Dissertations / Theses on the topic 'Temporal reasoning'
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Sripada, Suryanarayana Murthy. "Temporal reasoning in deductive databases." Thesis, Imperial College London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387841.
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Gago, M. Carmen FernaÌndez. "Efficient control of temporal reasoning." Thesis, University of Liverpool, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402682.
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Nilsson, Mikael. "Efficient Temporal Reasoning with Uncertainty." Licentiate thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119409.
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Automated Planning is an active area within Artificial Intelligence. With the help of computers we can quickly find good plans in complicated problem domains, such as planning for search and rescue after a natural disaster. When planning in realistic domains the exact duration of an action generally cannot be predicted in advance. Temporal planning therefore tends to use upper bounds on durations, with the explicit or implicit assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false. If we finish cooking too early, the dinner will be cold before everyone is at home and can eat. Simple Temporal Networks with Uncertainty (STNUs) allow us to model such situations. An STNU-based planner must verify that the temporal problems it generates are executable, which is captured by the property of dynamic controllability (DC). If a plan is not dynamically controllable, adding actions cannot restore controllability. Therefore a planner should verify after each action addition whether the plan remains DC, and if not, backtrack. Verifying dynamic controllability of a full STNU is computationally intensive. Therefore, incremental DC verification algorithms are needed. We start by discussing two existing algorithms relevant to the thesis. These are the very first DC verification algorithm called MMV (by Morris, Muscettola and Vidal) and the incremental DC verification algorithm called FastIDC, which is based on MMV. We then show that FastIDC is not sound, sometimes labeling networks as dynamically controllable when they are not. We analyze the algorithm to pinpoint the cause and show how the algorithm can be modified to correctly and efficiently detect uncontrollable networks. In the next part we use insights from this work to re-analyze the MMV algorithm. This algorithm is pseudo-polynomial and was later subsumed by first an n5 algorithm and then an n4 algorithm. We show that the basic techniques used by MMV can in fact be used to create an n4 algorithm for verifying dynamic controllability, with a new termination criterion based on a deeper analysis of MMV. This means that there is now a comparatively easy way of implementing a highly efficient dynamic controllability verification algorithm. From a theoretical viewpoint, understanding MMV is important since it acts as a building block for all subsequent algorithms that verify dynamic controllability. In our analysis we also discuss a change in MMV which reduces the amount of regression needed in the network substantially. In the final part of the thesis we show that the FastIDC method can result in traversing part of a temporal network multiple times, with constraints slowly tightening towards their final values. As a result of our analysis we then present a new algorithm with an improved traversal strategy that avoids this behavior. The new algorithm, EfficientIDC, has a time complexity which is lower than that of FastIDC. We prove that it is sound and complete.
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Hamlet, I. M. "Assumption based temporal reasoning in medicine." Thesis, University of Sussex, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235351.
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Evans, David Hugh. "An investigation of persistence in temporal reasoning." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267814.
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Tawfik, Ahmed Yassin. "Changing times, an investigation in probabilistic temporal reasoning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq23971.pdf.
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Hostetter, Michael. "Analogical representation in temporal, spatial, and mnemonic reasoning." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-03242009-040545/.
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Gao, Feng. "Complex medical event detection using temporal constraint reasoning." Thesis, University of Aberdeen, 2010. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=153271.
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The Neonatal Intensive Care Unit (NICU) is a hospital ward specializing in looking after premature and ill newborn babies. Working in such a busy and complex environment is not easy and sophisticated equipment is used to help the daily work of the medical staff . Computers are used to analyse the large amount of monitored data and extract hidden information, e.g. to detect interesting events. Unfortunately, one group of important events lacks features that are recognizable by computers. This group includes the actions taken by the medical sta , for example two actions related to the respiratory system: inserting an endotracheal tube into a baby’s trachea (ET Intubating) or sucking out the tube (ET Suctioning). These events are very important building blocks for other computer applications aimed at helping the sta . In this research, a strategy for detecting these medical actions based on contextual knowledge is proposed. This contextual knowledge specifies what other events normally occur with each target event and how they are temporally related to each other. The idea behind this strategy is that all medical actions are taken for di erent purposes hence may have di erent procedures (contextual knowledge) for performing them. This contextual knowledge is modelled using a point based framework with special attention given to various types of uncertainty. Event detection consists in searching for consistent matching between a model based on the contextual knowledge and the observed event instances - a Temporal Constraint Satisfaction Problem (TCSP). The strategy is evaluated by detecting ET Intubating and ET Suctioning events, using a specially collected NICU monitoring dataset. The results of this evaluation are encouraging and show that the strategy is capable of detecting complex events in an NICU.
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Shu, I.-hsiang 1979. "Enabling fast flexible planning through incremental temporal reasoning." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/18035.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (leaves 70-71).
In order for a team of autonomous agents to successfully complete its mission, the agents must be able to quickly re-plan on the fly as unforeseen events arise in the environment. This requires temporally flexible plans that allow the agent to adapt to execution uncertainties by not overcommitting on time constraints, and a continuous planner that replans at any point when the current plan fails. To achieve both of these requirements, planners must have the ability to reason quickly about timing constraints. This thesis provides a fast incremental algorithm, ITC, for determining the temporal consistency of temporally flexible plans. Additionally, the temporal reasoning capability of ITC is able to return the conflict or the nature of the inconsistency to the planner, such that the planner can resolve inconsistencies quickly and intelligently. The ITC algorithm combines the speed of shortest-path algorithms known to network optimization with the spirit of incremental algorithms such as Incremental A* and those used within truth maintenance systems (TMS). The algorithm has been implemented and integrated into a temporal planner, called Kirk. It has demonstrated an order of magnitude speed increase on cooperative air vehicle scenarios.
by I-hsiang Shu.
M.Eng.
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Castellini, Claudio. "Automated reasoning in quantified modal and temporal logics." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/753.
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This thesis is about automated reasoning in quantified modal and temporal logics, with an application to formal methods. Quantified modal and temporal logics are extensions of classical first-order logic in which the notion of truth is extended to take into account its necessity or equivalently, in the temporal setting, its persistence through time. Due to their high complexity, these logics are less widely known and studied than their propositional counterparts. Moreover, little so far is known about their mechanisability and usefulness for formal methods. The relevant contributions of this thesis are threefold: firstly, we devise a sound and complete set of sequent calculi for quantified modal logics; secondly, we extend the approach to the quantified temporal logic of linear, discrete time and develop a framework for doing automated reasoning via Proof Planning in it; thirdly, we show a set of experimental results obtained by applying the framework to the problem of Feature Interactions in telecommunication systems. These results indicate that (a) the problem can be concisely and effectively modeled in the aforementioned logic, (b) proof planning actually captures common structures in the related proofs, and (c) the approach is viable also from the point of view of efficiency.
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Brown, Daniel. "Temporal case-based reasoning for insulin decision support." Thesis, Oxford Brookes University, 2015. https://radar.brookes.ac.uk/radar/items/020befaf-009b-44ff-ac6d-4b9f2bcc21a0/1/.
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Type 1 diabetes mellitus is an autoimmune disease resulting in insufficient insulin to regulate blood glucose levels. The condition can be successfully managed through effective blood glucose control, one aspect of which is the administration of bolus insulin. Formulas exist to estimate the required bolus, and have been adopted by existing mobile expert systems. These formulas are shown to be effective but are unable to automatically adapt to an individual. This research resolves the limitations of existing formula based calculators by using case-based reasoning to automatically improve bolus advice. Case-based reasoning is a method of artificial intelligence that has successfully been adopted in the diabetes domain previously, but has primarily been limited to assisting doctors with therapy adjustments. Here case-based reasoning is instead used to directly assist the patient. The case-based reasoning process is enhanced for bolus advice through a temporal retrieval algorithm coupled with domain specic automated adjustment and revision. This temporal retrieval algorithm includes factors from previous events to improve the prediction of a bolus dose. The automated adjustment then refines the predicted bolus dose, and automated revision improves the prediction for future advice through the evaluation of the resulting blood glucose level. Analysis of the temporal retrieval algorithm found that it is capable of predicting bolus advice comparable to closed-loop simulation and existing formulas, with adapted advice resulting in improvements to simulated blood glucose control. The learning potential of the model is made evident through further improvements in blood glucose control when using revised advice. The system is implemented on a mobile device with a focus on safety using formal methods to help ensure actions performed do not violate the system constraints. Performance analysis demonstrated acceptable response times, providing evidence that this approach is viable. The research demonstrates how formula based mobile bolus calculators can be replaced by an artificially intelligent alternative which continuously learns to improve advice.
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Dufour-Lussier, Valmi. "Reasoning with qualitative spatial and temporal textual cases." Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0182/document.
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Cette thèse propose un modèle permettant la mise en œuvre d'un système de raisonnement à partir de cas capable d'adapter des procédures représentées sous forme de texte en langue naturelle, en réponse à des requêtes d'utilisateurs. Bien que les cas et les solutions soient sous forme textuelle, l'adaptation elle-même est d'abord appliquée à un réseau de contraintes temporelles exprimées à l'aide d'une algèbre qualitative, grâce à l'utilisation d'un opérateur de révision des croyances. Des méthodes de traitement automatique des langues sont utilisées pour acquérir les représentations algébriques des cas ainsi que pour regénérer le texte à partir du résultat de l'adaptationThis thesis proposes a practical model making it possible to implement a case-based reasoning system that adapts processes represented as natural language text in response to user queries. While the cases and the solutions are in textual form, the adaptation itself is performed on networks of temporal constraints expressed with a qualitative algebra, using a belief revision operator. Natural language processing methods are used to acquire case representations and to regenerate text based on the adaptation result
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Dufour-Lussier, Valmi. "Reasoning with qualitative spatial and temporal textual cases." Electronic Thesis or Diss., Université de Lorraine, 2014. http://www.theses.fr/2014LORR0182.
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Cette thèse propose un modèle permettant la mise en œuvre d'un système de raisonnement à partir de cas capable d'adapter des procédures représentées sous forme de texte en langue naturelle, en réponse à des requêtes d'utilisateurs. Bien que les cas et les solutions soient sous forme textuelle, l'adaptation elle-même est d'abord appliquée à un réseau de contraintes temporelles exprimées à l'aide d'une algèbre qualitative, grâce à l'utilisation d'un opérateur de révision des croyances. Des méthodes de traitement automatique des langues sont utilisées pour acquérir les représentations algébriques des cas ainsi que pour regénérer le texte à partir du résultat de l'adaptationThis thesis proposes a practical model making it possible to implement a case-based reasoning system that adapts processes represented as natural language text in response to user queries. While the cases and the solutions are in textual form, the adaptation itself is performed on networks of temporal constraints expressed with a qualitative algebra, using a belief revision operator. Natural language processing methods are used to acquire case representations and to regenerate text based on the adaptation result
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Bränd, Stefan. "Using Rigid Landmarks to Infer Inter-Temporal Spatial Relations in Spatio-Temporal Reasoning." Thesis, Linköpings universitet, Artificiell intelligens och integrerad datorsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-124064.
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Spatio-temporal reasoning is the area of automated reasoning about space and time and is important in the field of robotics. It is desirable for an autonomous robot to have the ability to reason about both time and space. ST0 is a logic that allows for such reasoning by, among other things, defining a formalism used to describe the relationship between spatial regions and a calculus that allows for deducing further information regarding such spatial relations. An extension of ST0 is ST1 that can be used to describe the relationship between spatial entities across time-points (inter-temporal relations) while ST0 is constrained to doing so within a single time-point. This allows for a better ability of expressing how spatial entities change over time. A major obstacle in using ST1 in practise however, is the fact that any observations made regarding spatial relations between regions is constrained to the time-point in which the observation was made, so we are unable to observe inter-temporal relations. Further complicating things is the fact that deducing such inter-temporal relations is not possible without a frame of reference. This thesis examines one method of overcoming these problems by considering the concept of rigid regions which are assumed to always be unchanging and using them as the frame of reference, or as landmarks. The effectiveness of this method is studied by conducting experiments where a comparison is made between various landmark ratios with respect to the total number of regions under consideration. Results show that when a high degree of intra-temporal relations are fully or partially known, increasing the number of landmark regions will reduce the percentage of inter-temporal relations to be completely unknown. Despite this, very few inter-temporal relations can be fully determined even with a high ratio of landmark regions.
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Nogueira, Vitor Beires. "Temporal reasoning in a logic programming language with modularity." Doctoral thesis, Universidade de Évora, 2008. http://hdl.handle.net/10174/11138.
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Actualmente os Sistemas de Informação Organizacionais (SIO) lidam cada vez mais com informação que tem dependências temporais. Neste trabalho concebemos um ambiente de trabalho para construir e manter SIO Temporais. Este ambiente assenta sobre um linguagem lógica denominada Temporal Contextua) Logic Programming que integra modularidade com raciocínio temporal fazendo com que a utilização de um módulo dependa do tempo do contexto. Esta linguagem é a evolução de uma outra, também introduzida nesta tese, que combina Contextua) Logic Programming com Temporal Annotated Constraint Logic Programming, na qual a modularidade e o tempo são características ortogonais. Ambas as linguagens são formalmente discutidas e exemplificadas.
As principais contribuições do trabalho descrito nesta tese incluem:
• Optimização de Contextua) Logic Programming (CxLP) através de interpretação abstracta.
• Sintaxe e semântica operacional para uma linguagem que combina de um modo independente as linguagens Temporal Annotated Constraint Logic Programming (TACLP) e CxLP. É apresentado um compilador para esta linguagem.
• Linguagem (sintaxe e semântica) que integra de um modo inovador modularidade (CxLP) com raciocínio temporal (TACLP). Nesta linguagem a utilização de um dado módulo está dependente do tempo do contexto. É descrito um interpretador e um compilador para esta linguagem.
• Ambiente de trabalho para construir e fazer a manutenção de SIO Temporais. Assenta sobre uma especificação revista da linguagem ISCO, adicionando classes e manipulação de dados temporais. É fornecido um compilador em que a linguagem resultante é a descrita no item anterior. ABSTRACT- Current Organisational Information Systems (OIS) deal with more and more Infor-mation that, is time dependent. In this work we provide a framework to construct and maintain Temporal OIS. This framework builds upon a logical language called Temporal Contextual. Logic Programming that deeply integrates modularity with tem-poral reasoning making the usage of a module time dependent. This language is an evolution of another one, also introduced in this thesis, that combines Contextual Logic Programming with Temporal Annotated Constraint Logic Programming where modularity and time are orthogonal features. Both languages are formally discussed and illustrated.
The main contributions of the work described in this thesis include:
• Optimisation of Contextual Logic Programming (CxLP) through abstract interpretation.
• Syntax and operational semantics for an independent combination of the temporal framework Temporal Annotated Constraint Logic Programming (TACLP) and CxLP. A compiler for this language is also provided.
• Language (syntax and semantics) that integrates in a innovative way modularity
(CxLP) with temporal reasoning (TACLP). In this language the usage of a given
module depends of the time of the context. An interpreter and a compiler for
this language are described.
• Framework to construct and maintain Temporal Organisational Information Systems. It builds upon a revised specification of the language ISCO, adding temporal classes and temporal data manipulation. A compiler targeting the language presented in the previous item is also given.
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de, Leng Daniel. "Spatio-Temporal Stream Reasoning with Adaptive State Stream Generation." Licentiate thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138645.
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A lot of today's data is generated incrementally over time by a large variety of producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, making sense of these streams of data through reasoning is challenging. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in a physical environment. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and its refinement an important problem. Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this thesis, we integrate techniques for logic-based spatio-temporal stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over streaming data and the problem of robustly managing streaming data and its refinement. The main contributions of this thesis are (1) a logic-based spatio-temporal reasoning technique that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt in situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in the context of a case study on run-time adaptive reconfiguration. The results show that the proposed system – by combining reasoning over and reasoning about streams – can robustly perform spatio-temporal stream reasoning, even when the availability of streaming resources changes.The series name Linköping Studies in Science and Technology Licentiate Thesis is inocorrect. The correct series name is Linköping Studies in Science and Technology Thesis.
NFFP6
CENIIT
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Broxvall, Mathias. "A Study in the Computational Complexity of Temporal Reasoning." Doctoral thesis, Linköping : Univ, 2002. http://www.ep.liu.se/diss/science_technology/07/79/index.html.
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Rodriguez, Moreno Diana V. "The dynamics of syllogistic reasoning : an fMRI investigation /." Access full-text from WCMC:, 2005. http://proquest.umi.com/pqdweb?did=1428837041&sid=5&Fmt=2&clientId=8424&RQT=309&VName=PQD.
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Sioutis, Michaël. "Algorithmic contributions to qualitative constraint-based spatial and temporal reasoning." Thesis, Artois, 2017. http://www.theses.fr/2017ARTO0401/document.
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Le raisonnement spatial et temporel qualitatif est un domaine principal d’études de l’intelligence artificielle et, en particulier, du domaine de la représentation des connaissances, qui traite des concepts cognitifs fondamentaux de l’espace et du temps de manière abstraite. Dans notre thèse, nous nous focalisons sur les formalismes du domaine du raisonnement spatial et temporel qualitatif représentant les informations par des contraintes et apportons des contributions sur plusieurs aspects. En particulier, étant donnée des bases de connaissances d’informations qualitatives sur l’espace ou le temps, nous définissons des nouvelles conditions de consistance locale et des techniques associées afin de résoudre efficacement les problèmes fondamentaux se posant. Nous traitons notamment du problème de la satisfiabilité qui est le problème de décider s’il existe une interprétation quantitative de toutes les entités satisfaisant l’ensemble des contraintes qualitatives. Nous considérons également le problème de l’étiquetage minimal qui consiste à déterminer pour toutes les contraintes qualitatives les relations de base participant à au moins une solution ainsi que le problème de redondance consistant à déterminer les contraintes qualitatives non redondantes. En outre, nous enrichissons le domaine des formalismes spatio-temporels par des contributions concernant une logique spatio-temporelle combinant la logique temporelle propositionnelle (PTL) avec un langage de contraintes qualitatives spatiales et une étude de la problématique consistant à gérer une séquence temporelle de configurations spatiales qualitatives devant satisfaire des contraintes de transitionQualitative Spatial and Temporal Reasoning is a major field of study in Artificial Intelligence and, particularly, in Knowledge Representation, which deals with the fundamental cognitive concepts of space and time in an abstract manner. In our thesis, we focus on qualitative constraint-based spatial and temporal formalisms and make contributions to several aspects. In particular, given a knowledge base of qualitative spatial or temporal information, we define novel local consistency conditions and related techniques to efficiently solve the fundamental reasoning problems that are associated with such knowledge bases. These reasoning problems consist of the satisfiability problem, which is the problem of deciding whether there exists a quantitative interpretation of all the entities of a knowledge base such that all of its qualitative relations are satisfied by that interpretation, the minimal labeling problem, which is the problem of determining all the atoms for each of the qualitative relations of a knowledge base that participate in at least one of its solutions, and the redundancy problem, which is the problem of obtaining all the non-redundant qualitative relations of a knowledge base. Further, we enrich the field of spatio-temporal formalisms that combine space and time in an interrelated manner by making contributions with respect to a qualitative spatio-temporal logic that results by combining the propositional temporal logic (PTL) with a qualitative spatial constraint language, and by investigating the task of ordering a temporal sequence of qualitative spatial configurations to meet certain transition constraints
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BERTAGNON, ALESSANDRO. "Improving Reasoning in Constraint Logic Programming: an Application to Route Planning and Qualitative Temporal Reasoning Problems." Doctoral thesis, Università degli studi di Ferrara, 2022. http://hdl.handle.net/11392/2487898.
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Constraint (Logic) Programming (CLP) is a popular paradigm to deal with Constraint Satisfaction Problems (CSPs) and Constraint Optimization Problems (COPs) in artificial intelligence. Constraint solving techniques, also known as constraint reasoning algorithms, can be divided into two distinct and orthogonal strategies: inference (or constraint propagation) and search. In this research we address constraint reasoning algorithms for two popular application domains: vehicle route planning and qualitative temporal reasoning. Regarding vehicle route planning, we study the Euclidean TSP (ETSP), a special case of the better known Traveling Salesperson Problem (TSP). Many real-life instances belong to the subclass of ETSP, where more information is available than in the general TSP: the nodes to be visited are points in the Euclidean plane, and the distance between them is the Euclidean distance.
The usual approach in constraint programming to solve the ETSP is to build a distance matrix, and then address the problem as a general TSP. Instead, in this work we propose to use geometric information, present in Euclidean TSP instances, to improve constraint propagation. We also apply machine learning techniques (random forests, neural networks) with the aim of imposing only the most efficient subset of constraints to increase overall solving performance. Qualitative temporal reasoning, on the other hand, is an area that has greatly benefited from constraint programming techniques since James F. Allen proposed an algebra, in 1983, that later became known as Allen’s Interval Algebra (IA). When the constraints of a problem concern the temporal relations between events, the problem is identified as temporal CSP. Branching Interval Algebra (BA) is the natural branching-time generalization of IA where time is no longer seen as a straight line but rather as a tree that can branch in the future. BA also has many potential applications in different areas of artificial intelligence; but unfortunately, the consistency problem of temporal CSPs expressed in BA is NP-hard, as in the linear case.
In order to be able to solve the consistency problem efficiently, one approach consists of exploiting the tractable fragments of the algebra. Here, we develop algorithms to study tractability of BA fragments and then we propose an enhanced version of a search algorithm exploiting such tractable fragments to improve its computational performance.La programmazione (logica) a vincoli (Constraint Logic Programming (CLP)) è un paradigma di programmazione nato per risolvere problemi di soddisfacimento di vincoli (Constraint Satisfaction Problem (CSP)) e problemi di ottimizzazione vincolata (Constraint Optimization Problem (COP)) in intelligenza artificiale. Le tecniche di risoluzione per i problemi di soddisfacimento di vincoli, dette anche di constraint reasoning, possono essere suddivise in due strategie distinte e ortogonali: inferenza (detta anche “propagazione dei vincoli”) e ricerca nello spazio degli stati. L’obiettivo della ricerca presentata in questa tesi è quello di sviluppare algoritmi di constraint reasoning per due popolari domini applicativi: la pianificazione dei percorsi dei veicoli e il ragionamento temporale qualitativo. Per quanto riguarda i problemi di pianificazione dei percorsi dei veicoli, studieremo il problema del commesso viaggiatore euclideo (Euclidean Traveling Salesperson Problem (ETSP)), un caso speciale del più noto problema del commesso viaggiatore (Traveling Salesperson Problem (TSP)). Molte istanze di problemi reali appartengono alla sottoclasse dell’ETSP, in cui i nodi da visitare sono punti nel piano euclideo, e la distanza tra loro è la distanza euclidea. L’approccio più comune in CLP per risolvere l’ETSP è quello di costruire una matrice di distanza, e poi affrontare il problema in modo più generale come un TSP. Invece, in questo lavoro proponiamo di utilizzare le informazioni geometriche, presenti nelle istanze dell’ETSP, per migliorare la propagazione dei vincoli. Applichiamo anche tecniche di apprendimento automatico (foreste casuali, reti neurali) con l’obiettivo di imporre solo il sottoinsieme più efficiente di vincoli per aumentare le prestazioni globali di risoluzione. Il ragionamento temporale qualitativo, d’altra parte, è un’area che ha notevolmente beneficiato delle tecniche di programmazione a vincoli da quando James F. Allen ha proposto un’algebra, nel 1983, che in seguito è diventata nota come Allen’s Interval Algebra (IA). Quando i vincoli di un problema riguardano le relazioni temporali tra eventi, il problema viene definito CSP temporale. La Branching Interval Algebra (BA) è la naturale generalizzazione della IA in cui il tempo non è più rappresentato come una linea retta ma piuttosto come un albero che può ramificarsi nel futuro. Anche BA ha molte potenziali applicazioni in diverse aree dell’intelligenza artificiale; ma sfortunatamente, il problema di coerenza dei CSP temporali espressi in BA è NP-difficile, come nel caso lineare. Per poter risolvere il problema di coerenza in modo efficiente, un approccio consiste nello sfruttare i frammenti trattabili dell’algebra. In questa tesi viene presentato uno studio sulla trattabilità di alcuni frammenti di BA e viene proposta una versione migliorata di un algoritmo di ricerca che sfruttando tali frammenti trattabili è in grado di ottenere migliori prestazioni computazionali.
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Mülâyim, Mehmet Oǧuz. "Anytime Case-Based Reasoning in Large-Scale Temporal Case Bases." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/671283.
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L'enfocament de la metodologia Casi-Based Reasoning (CBR) per a la resolució de problemes que "problemes similars tenen solucions similars" ha demostrat ser bastant favorable per a moltes aplicacions d'intel·ligència artificial industrial. No obstant això, els mateixos avantatges de CBR dificulten el seu acompliment ja que les bases de casos (CB) creixen més que mides raonables. Cercar casos similars és costós. Aquest desavantatge sovint fa que CBR sigui menys atractiu per als entorns de dades abundants d'avui dia, mentre que, en realitat, cada vegada hi ha més raons per beneficiar-se d'aquesta metodologia eficaç. En conseqüència, l'enfocament tradicional de la comunitat CBR de controlar el creixement de la CB per mantenir el rendiment està canviant cap a la recerca de noves formes de tractar amb dades abundants.
Com a contribució a aquests esforços, aquesta tesi té com a objectiu accelerar el CBR aprofitant tant els espais de problemes com els de solucions en els CB de gran escala que es componen de casos relacionats temporalment, com en l'exemple de les històries clíniques electròniques. Per a les ocasions en què l'acceleració que vam aconseguir per obtenir resultats exactes encara no sigui factible, dotem el sistema CBR amb capacitats d'algoritmes anytime per proporcionar resultats aproximats amb confiança en cas d'interrupció. Aprofitar la temporalitat dels casos ens permet assolir guanys superiors en el temps d'execució per als CB de milions de casos. Els experiments amb conjunts de dades del món real disponibles públicament fomenten l'ús continu de CBR en dominis en els quals CBR històricament sobresurt com l'atenció mèdica; i al seu torn, no patint, sinó gaudint del big data.El enfoque de la metodología Case-Based Reasoning (CBR) para la resolución de problemas de que "problemas similares tienen soluciones similares" ha demostrado ser bastante favorable para muchas aplicaciones de inteligencia artificial industrial. Sin embargo, las mismas ventajas de CBR dificultan su desempeño ya que las bases de casos (CB) crecen más que tamaños razonables. Buscar casos similares es costoso. Esta desventaja a menudo hace que CBR sea menos atractivo para los entornos de datos abundantes de hoy en día, mientras que, en realidad, cada vez hay más razones para beneficiarse de esta metodología eficaz. En consecuencia, el enfoque tradicional de la comunidad CBR de controlar el crecimiento de la CB para mantener el rendimiento está cambiando hacia la búsqueda de nuevas formas de tratar con datos abundantes. Como contribución a estos esfuerzos, esta tesis tiene como objetivo acelerar el CBR aprovechando tanto los espacios de problemas como los de soluciones en los CB de gran escala que se componen de casos relacionados temporalmente, como en el ejemplo de las historias clínicas electrónicas. Para las ocasiones en las que la aceleración que logramos para obtener resultados exactos aún no sea factible, dotamos al sistema CBR con capacidades de algoritmos anytime para proporcionar resultados aproximados con confianza en caso de interrupción. Aprovechar la temporalidad de los casos nos permite alcanzar ganancias superiores en el tiempo de ejecución para los CB de millones de casos. Los experimentos con conjuntos de datos del mundo real disponibles públicamente fomentan el uso continuo de CBR en dominios en los que CBR históricamente sobresale como la atención médica; y a su vez, no sufriendo, sino disfrutando del big data.
Case-Based Reasoning (CBR) methodology's approach to problem-solving that "similar problems have similar solutions" has proved quite favorable for many industrial artificial intelligence applications. However, CBR's very advantages hinder its performance as case bases (CBs) grow larger than moderate sizes. Searching similar cases is expensive. This handicap often makes CBR less appealing for today's ubiquitous data environments while, actually, there is ever more reason to benefit from this effective methodology. Accordingly, CBR community's traditional approach of controlling CB growth to maintain performance is shifting towards finding new ways to deal with abundant data. As a contribution to these efforts, this thesis aims to speed up CBR by leveraging both problem and solution spaces in large-scale CBs that are composed of temporally related cases, as in the example of electronic health records. For the occasions when the speed-up we achieve for exact results may still not be feasible, we endow the CBR system with anytime algorithm capabilities to provide approximate results with confidence upon interruption. Exploiting the temporality of cases allows us to reach superior gains in execution time for CBs of millions of cases. Experiments with publicly available real-world datasets encourage the continued use of CBR in domains where it historically excels like healthcare; and this time, not suffering from, but enjoying big data.
Universitat Autònoma de Barcelona. Programa de Doctorat en Informàtica
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Talbot, Christine. "Directing Virtual Humans Using Play-Scripts and Spatio-Temporal Reasoning." Thesis, The University of North Carolina at Charlotte, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10791242.
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Historically, most virtual human character research focuses on realism/emotions, interaction with humans, and discourse. The majority of the spatial positioning of characters has focused on one-on-one conversations with humans or placing virtual characters side-by-side when talking. These rely on conversation space as the main driver (if any) for character placement.
Movies and games rely on motion capture (mocap) files and hard-coded functions to perform spatial movements. These require extensive technical knowledge just to have a character move from one place to another. Other methods involve the use of Behavior Markup Language (BML), a form of XML, which describes character behaviors. BML Realizers take this BML and perform the requested behavior(s) on the character(s). Also, there are waypoint and other spatial navigation schemes, but they primarily focus on traversals and not correct positioning. Each of these require a fair amount of low-level detail and knowledge to write, plus BML realizers are still in their early stages of development.
Theatre, movies, and television all utilize a form of play-scripts, which provide detailed information on what the actor must do spatially, and when for a particular scene (that is spatio-temporal direction). These involve annotations, in addition to the speech, which identify scene setups, character movements, and entrances /exits. Humans have the ability to take these play-scripts and easily perform a believable scene.
This research focuses on utilizing play-scripts to provide spatio-temporal direction to virtual characters within a scene. Because of the simplicity of creating a playscript, and our algorithms to interpret the scripts, we are able to provide a quick method of blocking scenes with virtual characters.
We focus on not only an all-virtual cast of characters, but also human-controlled characters intermixing with the virtual characters for the scene. The key here is that human-controlled characters introduce a dynamic spatial component that affects how the virtual characters should perform the scene to ensure continuity, cohesion, and inclusion with the human-controlled character.
The algorithms to accomplish the blocking of a scene from a standard play-script are the core research contribution. These techniques include some part of speech tagging, named entity recognition, a rules engine, and strategically designed force-directed graphs. With these methods, we are able to similarly map any play-script’s spatial positioning of characters to a human-performed version of the same playscript. Also, human-based evaluations indicate these methods provide a qualitatively good performance.
Potential applications include: a rehearsal tool for actors; a director tool to help create a play-script; a controller for virtual human characters in games or virtual environments; or a planning tool for positioning people in an industrial environment.
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Abeysinghe, Geetha Kalyani. "Event calculus to support temporal reasoning in a clinical domain." Thesis, University of Southampton, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238888.
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El-Geresy, Baher. "Qualitative representation and reasoning for spatial and spatio-temporal systems." Thesis, University of South Wales, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403330.
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Blum, Anthony John. "An investigation into the psychology of spatial and temporal reasoning /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487841548269909.
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Legge, Gaynor W. "A Mechanism for Facilitating Temporal Reasoning in Discrete Event Simulation." Thesis, University of North Texas, 1992. https://digital.library.unt.edu/ark:/67531/metadc278352/.
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This research establishes the feasibility and potential utility of a software mechanism which employs artificial intelligence techniques to enhance the capabilities of standard discrete event simulators. As background, current methods of integrating artificial intelligence with simulation and relevant research are briefly reviewed.
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Peng, Taoxin. "A general approach to temporal reasoning about action and change." Thesis, University of Greenwich, 2001. http://gala.gre.ac.uk/6265/.
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Reasoning about actions and change based on common sense knowledge is one of the most important and difficult tasks in the artificial intelligence research area. A series of such tasks are identified which motivate the consideration and application of reasoning formalisms. There follows a discussion of the broad issues involved in modelling time and constructing a logical language. In general, worlds change over time. To model the dynamic world, the ability to predict what the state of the world will be after the execution of a particular sequence of actions, which take time and to explain how some given state change came about, i.e. the causality are basic requirements of any autonomous rational agent. The research work presented herein addresses some of the fundamental concepts and the relative issues in formal reasoning about actions and change. In this thesis, we employ a new time structure, which helps to deal with the so-called intermingling problem and the dividing instant problem. Also, the issue of how to treat the relationship between a time duration and its relative time entity is examined. In addition, some key terms for representing and reasoning about actions and change, such as states, situations, actions and events are formulated. Furthermore, a new formalism for reasoning about change over time is presented. It allows more flexible temporal causal relationships than do other formalisms for reasoning about causal change, such as the situation calculus and the event calculus. It includes effects that start during, immediately after, or some time after their causes, and which end before, simultaneously with, or after their causes. The presented formalism allows the expression of common-sense causal laws at high level. Also, it is shown how these laws can be used to deduce state change over time at low level. Finally, we show that the approach provided here is expressive.
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Rusmawati, Yanti. "Modelling and reasoning about dynamic networks as concurrent systems." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/modelling-and-reasoning-about-dynamic-networks-as-concurrent-systems(f6bd4a9c-e356-48ea-83a4-3d9d17c550c2).html.
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Highly dynamic and complex computing systems are increasingly needed and are relied upon in daily life. One such system is the dynamic network, particularly in communication, in which it has widespread applications, such as: Internet, peer-to-peer networks, mobile networks and wireless networks. Dynamic networks consist of nodes and edges whose operating status may change over time; the edges may be unreliable and operate intermittently. Message-passing in such networks is inherently difficult and reasoning about the behaviour of message-passing algorithms is also difficult and hard to analyse. Their behaviour and correctness are hard to formulate and establish. To undertake formal reasoning about such systems, abstract models are essential in order to separate the general reasoning about message routing and the updating of routing tables from the details of how these are implemented in particular networks. This thesis proposes a new approach to modelling and reasoning about dynamic networks as follows. It develops a series of abstract models which makes it possible to focus on the correctness of routing methods. It models the dynamic network as a “demonic” process which runs concurrently with routing updates and message-passing, to express dynamic networks as concurrent systems. This allows the use of temporal logic and fairness constraints to reason about dynamic networks. To do so, it introduces a modal logic and formulates concepts of fairness which capture network properties. The correctness of dynamic networks means that under certain conditions, all messages will eventually be delivered. Formulating networks as concurrent systems means can establish the correctness for networks that never cease to change. Modelling at that one level of abstraction means being able to prove the properties of networks independently of the mechanisms in actual networks. Therefore, it provides “a factorisation” of proofs of correctness for actual dynamic networks. The models are implemented as multi-threaded programs, and then adopted an experimental runtime verification tool called RULER to test whether model instances satisfy the modal correctness for message delivery.
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Hallin, Magnus. "SMT-Based Reasoning and Planning in TAL." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72596.
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Automated planning as a satisfiability problem is a method developed in theearly nineties. It has some known disadvantages, such as its inefficient encod-ing of numbers. The field of Satisfiability Modulo Teories tries to connectalready established solvers for e.g. linear constraints into SAT-solvers in orderto make reasoning about numerical values more efficient. This thesis combines planning as satisfiability and SMT to perform efficientreasoning about actions that occupy realistic time in Temporal Action Logic,a formalism developed at Linköping University for reasoning about action andchange.
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Lazarovski, Daniel. "Extending the Stream Reasoning in DyKnow with Spatial Reasoning in RCC-8." Thesis, Linköpings universitet, KPLAB - Laboratoriet för kunskapsbearbetning, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75885.
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Autonomous systems require a lot of information about the environment in which they operate in order to perform different high-level tasks. The information is made available through various sources, such as remote and on-board sensors, databases, GIS, the Internet, etc. The sensory input especially is incrementally available to the systems and can be represented as streams. High-level tasks often require some sort of reasoning over the input data, however raw streaming input is often not suitable for the higher level representations needed for reasoning. DyKnow is a stream processing framework that provides functionalities to represent knowledge needed for reasoning from streaming inputs. DyKnow has been used within a platform for task planning and execution monitoring for UAVs. The execution monitoring is performed using formula progression with monitor rules specified as temporal logic formulas. In this thesis we present an analysis for providing spatio-temporal functionalities to the formula progressor and we extend the formula progression with spatial reasoning in RCC-8. The result implementation is capable of evaluating spatio-temporal logic formulas using progression over streaming data. In addition, a ROS implementation of the formula progressor is presented as a part of a spatio-temporal stream reasoning architecture in ROS.Collaborative Unmanned Aircraft Systems (CUAS)
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Schultz, Carl 1984. "Methodologies for the development of qualitative spatial and temporal reasoning applications." Thesis, University of Auckland, 2010. http://hdl.handle.net/2292/6040.
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A great variety of scientific, engineering-based, and commercial application domains are fundamentally grounded in concepts of space and time. Over the last three decades there has been significant interest in more human-focused and intuitive qualitative spatial and temporal reasoning (QSTR) methods, which address the inherent limitations of purely numerical approaches for reasoning about space and time. However, despite the extremely significant theoretical advances that have been made in the QSTR field, there is a distinct absence of commercial and industrial applications that utilise QSTR calculi. The central issue is that relatively little research has addressed the unique challenges of designing and developing QSTR-based applications in comparison to more traditional systems that employ numerical processing techniques. The primary objective of this thesis is to support software engineering practitioners in the development of applications that utilise QSTR calculi. Five QSTR application case studies, which cover a range of diverse application domains, are presented and analysed throughout this thesis to motivate the development of effective methodologies. Furthermore, a comprehensive definition of QSTR applications is presented to provide a formal basis for establishing methodologies that address three major areas of QSTR application development: requirements specification, design, and validation. Design methodologies are presented that enable developers to evaluate the efficacy of numerous QSTR calculi with respect to QSTR application functional requirements. Additionally, the design methodologies adapt object-oriented concepts and machine learning techniques to facilitate the development of custom, high level, application-specific qualitative relations and constraints. Four key validation methodologies are adapted from well known techniques in software engineering: unit testing, integration testing, test coverage, and mutation testing. Furthermore, a novel metric called H-complexity is presented and used to define four additional test coverage classes that a developer can employ to assess the efficacy of a test suite. Finally, a meta-validation methodology is established that enables developers and the QSTR community to empirically investigate the efficacy of QSTR validation techniques. Experiments are conducted using the meta-validation methodology and the results are analysed to identify the most effective utilisation of QSTR validation methodologies according to the software development process being employed.
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Galushka, Mykola. "Discovering and managing similarity knowledge in temporal case-based reasoning systems." Thesis, University of Ulster, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535142.
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Suda, Martin [Verfasser], and Christoph [Akademischer Betreuer] Weidenbach. "Resolution-based methods for linear temporal reasoning / Martin Suda. Betreuer: Christoph Weidenbach." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2015. http://d-nb.info/1078261164/34.
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LI, Hongsheng. "An extended HD Fluent Analysis of Temporal knowledge in OWL-based clinical Guideline System." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/11742.
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The Web Ontology Language (OWL) based clinical guideline system is a kind of clinical decision support system which is often used to assist health professionals to find clinical recommendations from the guidelines and check clinical compliance issues in terms of the guideline recommendations. However, due to some limitations of the current OWL language constructs, temporal knowledge contained in various knowledge domains cannot be directly represented in OWL. As a result, the representation, query and reasoning of temporal knowledge are largely ignored in many OWL-based clinical guideline ontology systems. The aim of this research is to investigate a temporal knowledge modelling method namely “4D fluent” and extend it to represent the temporal constraints contained in clinical guideline recommendations within OWL language constructs. The extended 4D fluent method can model temporal constraints including valid calendar time, interval, duration, repetitive or cyclical temporal constraints and temporal relations such that it can enable reasoning over these temporal constraints in the OWL-based clinical guideline ontology system and overcome the shortcoming of the traditional OWL-based clinical guideline system to an extent.
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Leeser, Miriam Ellen. "Reasoning about the function and timing of integrated circuits with Prolog and temporal logic." Thesis, University of Cambridge, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.232797.
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The structure of circuits is specified with Prolog; their function and timing behaviour is specified with interval temporal logic. These structural and behavioural specifications are used to formally verify the functionality of circuit elements as well as their timing characteristics. A circuit is verified by deriving its behaviour from the behaviour of its components. The derived results can be abstracted to functional descriptions with timing constraints. The functional descriptions can then be used in proofs of more complex hardware circuits. Verification is done hierarchically, with transistors as primitive elements. Transistors are modeled as switch-level devices with delay. In order to model delay, the direction of signal flow through each transistor must be assigned. This is done automatically by a set of Prolog routines which also determine the inputs and outputs of each circuit component. Interval temporal logic descriptions are expressed in Prolog and manipulated using PALM: Prolog Assistant for Logic Manipulation. With PALM, the user specifies rewrite rules and uses these rules to manipulate logical terms. In the case of reasoning about circuits, PALM is used to manipulate the temporal logic descriptions of the components to derive a temporal logic description of the circuit. These techniques are demonstrated by applying them to several commonly used complementary metal oxide semiconductor (CMOS) structures. Examples include a fully complementary dynamic latch and a 1-bit adder. Both these circuits are implemented with transistors and exploit 2-phase clocking and charge sharing. The 1-bit adder is a sophisticated full adder implemented with a dynamic CMOS design style. The derived timing and functional behaviour of the 1-bit adder is abstracted to a purely functional behaviour which can be used to derive the behaviour of an arbitrary n-bit adder.
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Borges, Rafael. "A neural-symbolic system for temporal reasoning with application to model verification and learning." Thesis, City University London, 2012. http://openaccess.city.ac.uk/1303/.
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The effective integration of knowledge representation, reasoning and learning into a robust computational model is one of the key challenges in Computer Science and Artificial Intelligence. In particular, temporal models have been fundamental in describing the behaviour of Computational and Neural-Symbolic Systems. Furthermore, knowledge acquisition of correct descriptions of the desired system’s behaviour is a complex task in several domains. Several efforts have been directed towards the development of tools that are capable of learning, describing and evolving software models. This thesis contributes to two major areas of Computer Science, namely Artificial Intelligence (AI) and Software Engineering. Under an AI perspective, we present a novel neural-symbolic computational model capable of representing and learning temporal knowledge in recurrent networks. The model works in integrated fashion. It enables the effective representation of temporal knowledge, the adaptation of temporal models to a set of desirable system properties and effective learning from examples, which in turn can lead to symbolic temporal knowledge extraction from the corresponding trained neural networks. The model is sound, from a theoretical standpoint, but is also tested in a number of case studies. An extension to the framework is shown to tackle aspects of verification and adaptation under the SE perspective. As regards verification, we make use of established techniques for model checking, which allow the verification of properties described as temporal models and return counter-examples whenever the properties are not satisfied. Our neural-symbolic framework is then extended to deal with different sources of information. This includes the translation of model descriptions into the neural structure, the evolution of such descriptions by the application of learning of counter examples, and also the learning of new models from simple observation of their behaviour. In summary, we believe the thesis describes a principled methodology for temporal knowledge representation, learning and extraction, shedding new light on predictive temporal models, not only from a theoretical standpoint, but also with respect to a potentially large number of applications in AI, Neural Computation and Software Engineering, where temporal knowledge plays a fundamental role.
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Wu, Jing. "A qualitative spatio-temporal modelling and reasoning approach for the representation of moving entities." Thesis, Brest, 2015. http://www.theses.fr/2015BRES0036/document.
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La recherche développée dans cette thèse introduit une approche qualitative pour représenter et raisonner à partir d'entités spatiales dans un espace géographique à deux dimensions. Les patrons de mouvements entre entités dynamiques sont catégorisés à partir d'un modèle qualitatif de relations topologiques entre une ligne orientée et une région, et de relations d'orientation entre deux lignes orientées, respectivement. Les mouvements qualitatifs sont dérivés à partir de relations spatio-temporelles qui caractérisent des entités dynamiques conceptualisées comme des points ou des régions dans un espace à deux dimensions. Cette architecture de raisonnement permet de dériver des configurations de mouvements basiques dérivées à partir d'entités statiques et dynamiques. L'approche est complétée par une qualification de ces configurations à partir d'expressions du langage naturel. Les compositions de mouvements sont étudiées tout comme les transitions possibles dans des cas de données incomplètes. Les tables de compositions sont également explorées et permettent d'étendre les possibilités de raisonnement. Le modèle est expérimenté dans le contexte de l'analyse de trajectoires aériennes et maritimesThe research developed in this thesis introduces a qualitative approach for representing and reasoning on moving entities in a two-dimensional geographical space. Movement patterns of moving entities are categorized based on a series of qualitative spatial models of topological relations between a directed line and a region, and orientation relations between two directed lines, respectively. Qualitative movements are derived from the spatio-temporal relations that characterize moving entities conceptualized as either points or regions in a two-dimensional space. Such a spatio-temporal framework supports the derivation of the basic movement configurations inferred from moving and static entities. The approach is complemented by a tentative qualification of the possible natural language expressions of the primitive movements identified. Complex movements can be represented by a composition of these primitive movements. The notion of conceptual transition that favors the exploration of possible trajectories in the case of incomplete knowledge configurations is introduced and explored.Composition tables are also studied and provide additional reasoning capabilities. The whole approach is applied to the analysis of flight patterns and maritime trajectories
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Beaumont, Matthew, and n/a. "Handling Over-Constrained Temporal Constraint Networks." Griffith University. School of Information Technology, 2004. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20041213.084512.
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Temporal reasoning has been an active research area for over twenty years, with most work focussing on either enhancing the efficiency of current temporal reasoning algorithms or enriching the existing algebras. However, there has been little research into handling over-constrained temporal problems except to recognise that a problem is over-constrained and then to terminate. As many real-world temporal reasoning problems are inherently over-constrained, particularly in the scheduling domain, there is a significant need for approaches that can handle over-constrained situations. In this thesis, we propose two backtracking algorithms to gain partial solutions to over-constrained temporal problems. We also propose a new representation, the end-point ordering model, to allow the use of local search algorithms for temporal reasoning. Using this model we propose a constraint weighting local search algorithm as well as tabu and random-restart algorithms to gain partial solutions to over-constrained temporal problems. Specifically, the contributions of this thesis are: The introduction and empirical evaluation of two backtracking algorithms to solve over-constrained temporal problems. We provide two backtracking algorithms to close the gap in current temporal research to solve over-constrained problems; The representation of temporal constraint networks using the end-point ordering model. As current representation models are not suited for local search algorithms, we develop a new model such that local search can be applied efficiently to temporal reasoning; The development of a constraint weighting local search algorithm for under-constrained problems. As constraint weighting has proven to be efficient for solving many CSP problems, we implement a constraint weighting algorithm to solve under-constrained temporal problems; An empirical evaluation of constraint weighting local search against traditional backtracking algorithms. We compare the results of a constraint weighting algorithm with traditional backtracking approaches and find that in many cases constraint weighting has superior performance; The development of a constraint weighting local search, tabu search and random-restart local search algorithm for over-constrained temporal problems. We extend our constraint weighting algorithm to solve under-constrained temporal problems as well as implement two other popular local search algorithms: tabu search and random-restart; An empirical evaluation of all three local search algorithms against the two backtracking algorithms. We compare the results of all three local search algorithms with our twobacktracking algorithms for solving over-constrained temporal reasoning problems and find that local search proves to be considerably superior.
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Beaumont, Matthew. "Handling Over-Constrained Temporal Constraint Networks." Thesis, Griffith University, 2004. http://hdl.handle.net/10072/366603.
Full textAbstract:
Temporal reasoning has been an active research area for over twenty years, with most work focussing on either enhancing the efficiency of current temporal reasoning algorithms or enriching the existing algebras. However, there has been little research into handling over-constrained temporal problems except to recognise that a problem is over-constrained and then to terminate. As many real-world temporal reasoning problems are inherently over-constrained, particularly in the scheduling domain, there is a significant need for approaches that can handle over-constrained situations. In this thesis, we propose two backtracking algorithms to gain partial solutions to over-constrained temporal problems. We also propose a new representation, the end-point ordering model, to allow the use of local search algorithms for temporal reasoning. Using this model we propose a constraint weighting local search algorithm as well as tabu and random-restart algorithms to gain partial solutions to over-constrained temporal problems. Specifically, the contributions of this thesis are: The introduction and empirical evaluation of two backtracking algorithms to solve over-constrained temporal problems. We provide two backtracking algorithms to close the gap in current temporal research to solve over-constrained problems; The representation of temporal constraint networks using the end-point ordering model. As current representation models are not suited for local search algorithms, we develop a new model such that local search can be applied efficiently to temporal reasoning; The development of a constraint weighting local search algorithm for under-constrained problems. As constraint weighting has proven to be efficient for solving many CSP problems, we implement a constraint weighting algorithm to solve under-constrained temporal problems; An empirical evaluation of constraint weighting local search against traditional backtracking algorithms. We compare the results of a constraint weighting algorithm with traditional backtracking approaches and find that in many cases constraint weighting has superior performance; The development of a constraint weighting local search, tabu search and random-restart local search algorithm for over-constrained temporal problems. We extend our constraint weighting algorithm to solve under-constrained temporal problems as well as implement two other popular local search algorithms: tabu search and random-restart; An empirical evaluation of all three local search algorithms against the two backtracking algorithms. We compare the results of all three local search algorithms with our twobacktracking algorithms for solving over-constrained temporal reasoning problems and find that local search proves to be considerably superior.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Integrated and Intelligent Systems
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Lu, Zhirui. "Multi-valued temporal logic based reasoning system with applications to decision support in intelligent environments." Thesis, University of Ulster, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.550789.
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This work deals with decision-making problems with uncertain information in dynamic environment. It develops a new logic system, multi-valued temporal propositional logic, combining multi-valued logic and linear temporal logic. This new logic allows uncertain information to be represented with either a numerical truth value in the [0,1] interval or a linguistic value, and uses these values with both states and same-time and next-time rules. Multi-valued temporal propositional logic, a generic logic system, provides a simple calculus for analysing uncertain information with Lukasiewicz implication algebra. It introduces uncertainty and temporality into rules. Soundness and completeness theorems provide a theoretical foundation for the reasoning system. Based on the new logic, forward and backward reasoning algorithms are proposed, which offers simulation/prediction and query answering functions. The reasoning system, based on the forward and backward reasoning algorithms was programmed in Pro log. Three scenarios were then used to evaluate this reasoning system. The results of the evaluations showed that the proposed reasoning system could return reliable and reasonable feedback to users on their input. Furthermore, users are able to perfect their knowledge bases according to the feedback from the reasoning system on their input. A general comparison between the reasoning system and dynamic Bayesian networks with a simple scenario with uncertain information in a certain temporal environment was undertaken. Within this comparison, an analysis of advantages and disadvantages between the proposed reasoning system and dynamic ~ Bayesian networks has been provided.
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Alsarhani, Sami. "Reasoning about history based access control policy using past time operators of interval temporal logic." Thesis, De Montfort University, 2014. http://hdl.handle.net/2086/10406.
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Interval Temporal Logic (ITL) is a flexible notation for the propositional and first-order logical reasoning about periods of time that exist in specifications of hardware and software systems. ITL is different from other temporal logics since it can deal with both sequential and parallel composition and provides powerful and extensible specification and verification methods for reasoning about properties such as safety, time projection and liveness. Most imperative programming constructs can be seen as ITL formula that form the basis of an executable framework called Tempura that is used for the development and testing of ITL specifications.\\ ITL has only future operators, but the use of past operators make specifications referring to history more succinct; that is, there are classes of properties that can be expressed by means of much shorter formulas. What is more, statements are easier to express (simplicity) when past operators are included. Moreover, using past operators does not increase the complexity of interval temporal logic regarding the formula size and the simplicity. This thesis introduces past time of interval temporal logic where, instead of future time operators Chop, Chopstar, and Skip, we have past operators past Chop, past Chopstar and past Skip. The syntax and semantics of past time ITL are given together with its axiom and proof system. Furthermore, Security Analysis Toolkit for Agents (SANTA) operators such always-followed-by and the strong version of it has been given history based semantics using past time operators. In order to evaluate past time interval temporal logic, the problem of specification, verification of history based access control policies has been selected. This problem has already been solved using future time of interval temporal logic ITL but the drawback is that policy rules are not succinct and simple. However, the use of past time operators of ITL produces simple and succinct policy rules. The verification technique used to proof the safety property of history based access control policies is adapted for past time ITL to show that past time operators of interval temporal logic can specify and verify a security scenario such as history based access control policy.
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Rasmussen, Louise J. "THE EFFECTS OF REPRESENTATIONAL FORMAT AND DISCOURSE PRINCIPLES ON THE COMPREHENSION AND PRODUCTION OF TEMPORAL ORDER." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1190080849.
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Balser, Michael [Verfasser]. "Verifying Concurrent Systems with Symbolic Execution : Temporal Reasoning is Symbolic Execution with a Little Induction / Michael Balser." Aachen : Shaker, 2006. http://d-nb.info/1170528821/34.
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Martiny, Karsten [Verfasser]. "PDT logic : a probabilistic doxastic temporal logic for reasoning about beliefs in multi-agent systems / Karsten Martiny." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2018. http://d-nb.info/1152030132/34.
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Mas, i. Casals Orestes. "Sistemas difusos dinámicos para el tratamiento de información temporal imprecisa." Doctoral thesis, Universitat Politècnica de Catalunya, 1997. http://hdl.handle.net/10803/6914.
Full textAbstract:
Desde su aparición a mediados de los años 60, la Teoría de Conjuntos Difusos se ha venido aplicando con éxito a la resolución de problemas en ámbitos muy diversos, que resultan difíciles de tratar con los métodos clásicos, principalmente por la presencia de incertidumbres no aleatorias en su descripción. En estos casos, el problema no tiene una solución cerrada en forma de expresión matemática, pero sí suele tenerla en forma de un conjunto de reglas expresadas en lenguaje natural y, por consiguiente, impreciso. Un ejemplo típico es el problema de conducir un automóvil.En el ámbito de la ingeniería, el núcleo de cualquier solución difusa actual es un sistema lógico difuso, encargado de obtener las salidas a partir de las entradas en un proceso de tres etapas: füzzificación, inferencia y desfuzzifícación. Hasta la fecha, la totalidad de sistemas difusos efectúan sus razonamientos basándose solamente en los valores actuales de las entradas. Ello ha dado como resultado que los sistemas de inferencia difusa sean, desde el punto de vista matemático, sistemas no lineales algebraicos. Este hecho contrasta fuertemente con el entorno en que dichos sistemas suelen emplearse. En efecto, la mayoría de aplicaciones se construyen y utilizan en entornos dinámicos, los cuales son capaces de presentar comportamientos mucho más complejos que los sistemas estáticos. Cabe entonces preguntarse si el uso de sistemas difusos dinámicos -es decir, aquellos en que sus salidas dependan no sólo de los valores presentes de las entradas sino también de los pasados-, aportaría mejoras respecto a las soluciones difusas actuales.
En esta tesis se ha desarrollado una metodología para incorporar conceptos temporales difusos a los sistemas de inferencia difusa tradicionales. Para ello se ha propuesto una forma simple y eficaz de representar los citados conceptos en un entorno de ingeniería. Posteriormente se ha mostrado cómo introducirlos en las reglas difusas tradicionales, y se ha desarrollado un algoritmo para efectuar la inferencia en esta nueva situación. Se obtienen finalmente dos algoritmos distintos para dos casos diferenciados, pero ambas expresiones presentan la interesante propiedad de poder interpretarse como una convolución, tradicional en uno de los casos y una nueva forma que hemos denominado convolution difusa para el otro caso. Estas expresiones se pueden realizar por tanto de una forma muy elegante mediante circuitos analógicos o digitales.
La metodología desarrollada requiere que los conceptos temporales difusos que se manejan deban realizarse mediante la respuesta impulsional de un circuito lineal. Ello remite al problema del diseño de filtros desde el punto de vista temporal, mucho menos estudiado que desde el punto de vista frecuencial. A resultas de ello se dedica una parte de la presente tesis a establecer las pautas a seguir en el proceso de diseño de dichos filtros, valiéndose de técnicas de aproximación y de optimización.
Finalmente se presentan un ejemplo de aplicación, de interés tanto teórico como práctico. En él se presenta un sistema de reconocimiento simple de comandos verbales, basado en las técnicas propuestas en la presente tesis. Los resultados obtenidos han mostrado que con una estructura muy simple es posible obtener una discriminación más que suficiente entre las órdenes programadas, con la ventaja que presenta el realizar el sistema de forma totalmente analógica.
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Kreutzmann, Arne [Verfasser], Christian [Akademischer Betreuer] Freksa, and Alessandro [Akademischer Betreuer] Saffiotti. "Qualitative Spatial and Temporal Reasoning based on And/Or Linear Programming : an approach to partially grounded qualitative spatial reasoning / Arne Kreutzmann. Gutachter: Christian Freksa ; Alessandro Saffiotti. Betreuer: Christian Freksa." Bremen : Staats- und Universitätsbibliothek Bremen, 2014. http://d-nb.info/1072226669/34.
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Cohen-Solal, Quentin. "Un cadre algébrique pour le raisonnement qualitatif en présence d'informations hétérogènes : application aux raisonnements multi-échelle et spatio-temporel." Thesis, Normandie, 2017. http://www.theses.fr/2017NORMC245/document.
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Parmi les différentes formes de raisonnement étudiées dans le contexte de l'intelligence artificielle, le raisonnement qualitatif permet d'inférer de nouvelles connaissances dans le contexte d'informations imprécises, incomplètes et dépourvues de valeurs numériques. Il permet par exemple de déduire de nouvelles informations à partir d'un ensemble d'informations spatiales telles que « la France est frontalière de l'Allemagne », « la Suisse est à l'est de la France », « l'Italie est en Europe » et « le Luxembourg est proche de la France ». Il peut également être utilisé pour résoudre des abstractions de problèmes quantitatifs difficiles à résoudre, afin par exemple d'accélérer la résolution de ces problèmes.De nombreux formalismes de raisonnement qualitatif ont été proposés dans la littérature. Ils ne se focalisent cependant que sur un seul aspect du monde, alors que la majorité des applications requièrent la prise en compte d'informations hétérogènes. Afin de répondre à ces besoins, plusieurs combinaisons et extensions de formalismes qualitatifs, comme le raisonnement spatio-temporel et le raisonnement multi-échelle, ont récemment été proposées dans la littérature. Le raisonnement spatio-temporel permet de raisonner dans le contexte d'informations spatiales et temporelles interdépendantes. Le raisonnement multi-échelle permet de raisonner avec des informations de précisions différentes, et en particulier de lever des incohérences apparentes.Dans cette thèse, nous nous intéressons au raisonnement multi-échelle, au raisonnement spatio-temporel et aux combinaisons de formalismes qualitatifs.Nous proposons d'étendre le raisonnement qualitatif temporel multi-échelle pour prendre en compte le fait que les intervalles de temps peuvent être perçus comme des instants à certaines échelles de précision, de formaliser intégralement ce raisonnement et d'étudier la décision de la cohérence dans ce contexte ainsi que sa complexité. Nous montrons en particulier que ce formalisme permet de décider la cohérence et que le problème de décision de la cohérence est NP-complet, même dans le cas le plus simple.En outre, nous proposons un cadre général permettant de raisonner sur les séquences temporelles d'informations qualitatives, une forme de description spatio-temporelle. Ce cadre permet notamment de raisonner dans le contexte d'évolutions complexes. Par exemple, les entités considérées peuvent avoir des caractéristiques préservées au cours du temps, évoluer de manière dépendante les unes par rapport aux autres, tout en ayant un comportement potentiellement irréversible et différent selon leur nature. De plus, dans ce cadre, le raisonnement est plus performant computationnellement que les approches de l'état de l'art. Nous étudions en particulier la décision de la cohérence dans le contexte spécifique de régions mobiles de taille constante, et montrons que ce cadre permet effectivement de décider la cohérence.De surcroît, nous proposons un cadre formel unifiant plusieurs formes d'extensions et de combinaisons de formalismes qualitatifs, incluant le raisonnement multi-échelle et les séquences temporelles. Ce cadre permet de raisonner dans le contexte de chacune de ces combinaisons et extensions, mais également d'étudier de manière unifiée la décision de la cohérence et sa complexité. Nous établissons en particulier deux théorèmes complémentaires garantissant que la décision de la cohérence est polynomiale, et nous les utilisons pour prouver que plusieurs fragments de séquences temporelles sont traitables.Nous généralisons également la définition principale de formalisme qualitatif afin d'inclure des formalismes qualitatifs exclus des définitions de la littérature, importants dans le cadre des combinaisonsIn this thesis, we are interested in qualitative multi-scale reasoning, qualitative spatio-temporal reasoning and combinations of qualitative formalisms.We propose to extend the multiscale temporal reasoning to take into account the fact that time intervals can be perceived as instants at certain scales of precision, to fully formalize this reasoning and to study its consistency problem. We show in particular that this formalism decides consistency and that the consistency problem is NP-complete, even in the simplest case.In addition, we propose a general framework for reasoning on temporal sequences of qualitative information, a form of spatio-temporal description. This framework allows for reasoning in the context of complex evolutions. For example, the considered entities may have characteristics preserved over time, evolve in a dependent manner with respect to each other, while having a potentially irreversible and different behavior depending on their nature. Moreover, in this context, reasoning is computationally more efficient than state-of-the-art approaches. In particular, we study the consistency problem in the specific context of constant-size moving regions, and show that this framework actually decides consistency.Furthermore, we propose a formal framework unifying several forms of extensions and combinations of qualitative formalisms, including multi-scale reasoning and temporal sequences. This framework allows one to reason in the context of each of these combinations and extensions, but also to study in a unified way the consistency problem. In particular, we establish two complementary theorems guaranteeing that the consistency problem is polynomial, and we use them to prove that several fragments of temporal sequences are tractable
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Azmat, Shoaib. "Multilayer background modeling under occlusions for spatio-temporal scene analysis." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54005.
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This dissertation presents an efficient multilayer background modeling approach to distinguish among midground objects, the objects whose existence occurs over varying time scales between the extremes of short-term ephemeral appearances (foreground) and long-term stationary persistences (background). Traditional background modeling separates a given scene into foreground and background regions. However, the real world can be much more complex than this simple classification, and object appearance events often occur over varying time scales. There are situations in which objects appear on the scene at different points in time and become stationary; these objects can get occluded by one another, and can change positions or be removed from the scene. Inability to deal with such scenarios involving midground objects results in errors, such as ghost objects, miss-detection of occluding objects, aliasing caused by the objects that have left the scene but are not removed from the model, and new objects’ detection when existing objects are displaced. Modeling temporal layers of multiple objects allows us to overcome these errors, and enables the surveillance and summarization of scenes containing multiple midground objects.
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Rodrigues, Teresa Raquel. "O impacto da aprendizagem musical no desempenho de habilidades cognitivas implicadas na matemática." Master's thesis, Universidade de Évora, 2011. http://hdl.handle.net/10174/12025.
Full textAbstract:
Este trabalho tem como objectivo estudar o impacto da aprendizagem musical ao nível das habilidades
cognitivas e correspondência com o desempenho académico na matemática. Neste sentido, o presente propõese
analisar a relação entre a aptidão musical, a aptidão matemática e o raciocínio espacial-temporal. Posto isto,
recorrer-se-á à aplicação das sub-escalas de Aritmética e Composição de Objectos da Escala da Inteligência de
Weschler para Crianças - 3ª Edição (WISC-III), com crianças do 1º ciclo do Ensino Básico: um grupo que
frequenta o ensino vocacional de música e um segundo grupo sem treino musical. Serão também consideradas
medidas de desempenho académico e de desempenho musical recolhidos através de um questionário. Os
resultados indicam que os participantes com treino musical apresentam scores significativamente mais elevados
no subteste; ### ABSTRACT: The main aim of this work is to study the impact of music training in terms of cognitive skills and
correspondence with academic performance in mathematics. One proposes to analyse the relationship between
musical skills, mathematics abilities’ and spatial-temporal reasoning. According to this, the Arithmetic and Object
Assembly subscales from the Weschler Intelligence Scale for Children – 3rd. Edition (WISC-III) are applied to
children from the 1st. (Primary) Cycle of basic education: a group that attends vocational music education and a
second group with no musical training. In addition, measures of academic achievement and musical performance
will be considered through the use of a short questionnaire. Results indicate that the participants with musical
training present significantly higher scores in the arithmetic subtest as well as in mathematics. However, the
relationship between musical skills and spatial-temporal reasoning involved in mathematics did not show
significance at all.
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Preusse, Franziska [Verfasser], Der Meer Elke [Akademischer Betreuer] Van, Isabell [Akademischer Betreuer] Wartenburger, and Roland [Akademischer Betreuer] Grabner. "High fluid intelligence and analogical reasoning : behavioural and cerebral correlates and their temporal characteristics / Franziska Preusse. Gutachter: Elke van der Meer ; Isabell Wartenburger ; Roland Grabner." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2011. http://d-nb.info/1018232516/34.
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