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1
Brockmans, Sara. "Metamodel-based Knowledge Representation." [S.l. : s.n.], 2007. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000007322.
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2
Schlobach, Klaus Stefan. "Knowledge discovery in hybrid knowledge representation systems." Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272023.
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3
au, skhor@iinet net, and Sebastian Wankun Khor. "A Fuzzy Knowledge Map Framework for Knowledge Representation." Murdoch University, 2007. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20070822.32701.
Повний текст джерелаАнотація:
Cognitive Maps (CMs) have shown promise as tools for modelling and simulation of knowledge in computers as representation of real objects, concepts, perceptions or events and their relations. This thesis examines the application of fuzzy theory to the expression of these relations, and investigates the development of a framework to better manage the operations of these relations.
The Fuzzy Cognitive Map (FCM) was introduced in 1986 but little progress has been made since. This is because of the difficulty of modifying or extending its reasoning mechanism from causality to relations other than causality, such as associative and deductive reasoning. The ability to express the complex relations between objects and concepts determines the usefulness of the maps. Structuring these concepts and relations in a model so that they can be consistently represented and quickly accessed and anipulated by a computer is the goal of knowledge representation. This forms the main motivation of this research.
In this thesis, a novel framework is proposed whereby single-antecedent fuzzy rules can be applied to a directed graph, and reasoning ability is extended to include noncausality. The framework provides a hierarchical structure where a graph in a higher layer represents knowledge at a high level of abstraction, and graphs in a lower layer represent the knowledge in more detail. The framework allows a modular design of knowledge representation and facilitates the creation of a more complex structure for modelling and reasoning.
The experiments conducted in this thesis show that the proposed framework is effective and useful for deriving inferences from input data, solving certain classification problems, and for prediction and decision-making.
4
Khor, Sebastian W. "A fuzzy knowledge map framework for knowledge representation /." Access via Murdoch University Digital Theses Project, 2006. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20070822.32701.
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5
Khor, Sebastian Wankun. "A fuzzy knowledge map framework for knowledge representation." Thesis, Khor, Sebastian Wankun (2007) A fuzzy knowledge map framework for knowledge representation. PhD thesis, Murdoch University, 2007. https://researchrepository.murdoch.edu.au/id/eprint/129/.
Повний текст джерелаАнотація:
Cognitive Maps (CMs) have shown promise as tools for modelling and simulation of knowledge in computers as representation of real objects, concepts, perceptions or events and their relations. This thesis examines the application of fuzzy theory to the expression of these relations, and investigates the development of a framework to better manage the operations of these relations.
The Fuzzy Cognitive Map (FCM) was introduced in 1986 but little progress has been made since. This is because of the difficulty of modifying or extending its reasoning mechanism from causality to relations other than causality, such as associative and deductive reasoning. The ability to express the complex relations between objects and concepts determines the usefulness of the maps. Structuring these concepts and relations in a model so that they can be consistently represented and quickly accessed and anipulated by a computer is the goal of knowledge representation. This forms the main motivation of this research.
In this thesis, a novel framework is proposed whereby single-antecedent fuzzy rules can be applied to a directed graph, and reasoning ability is extended to include noncausality. The framework provides a hierarchical structure where a graph in a higher layer represents knowledge at a high level of abstraction, and graphs in a lower layer represent the knowledge in more detail. The framework allows a modular design of knowledge representation and facilitates the creation of a more complex structure for modelling and reasoning.
The experiments conducted in this thesis show that the proposed framework is effective and useful for deriving inferences from input data, solving certain classification problems, and for prediction and decision-making.
6
Khor, Sebastian Wankun. "A fuzzy knowledge map framework for knowledge representation." Khor, Sebastian Wankun (2007) A fuzzy knowledge map framework for knowledge representation. PhD thesis, Murdoch University, 2007. http://researchrepository.murdoch.edu.au/129/.
Повний текст джерелаАнотація:
Cognitive Maps (CMs) have shown promise as tools for modelling and simulation of knowledge in computers as representation of real objects, concepts, perceptions or events and their relations. This thesis examines the application of fuzzy theory to the expression of these relations, and investigates the development of a framework to better manage the operations of these relations.
The Fuzzy Cognitive Map (FCM) was introduced in 1986 but little progress has been made since. This is because of the difficulty of modifying or extending its reasoning mechanism from causality to relations other than causality, such as associative and deductive reasoning. The ability to express the complex relations between objects and concepts determines the usefulness of the maps. Structuring these concepts and relations in a model so that they can be consistently represented and quickly accessed and anipulated by a computer is the goal of knowledge representation. This forms the main motivation of this research.
In this thesis, a novel framework is proposed whereby single-antecedent fuzzy rules can be applied to a directed graph, and reasoning ability is extended to include noncausality. The framework provides a hierarchical structure where a graph in a higher layer represents knowledge at a high level of abstraction, and graphs in a lower layer represent the knowledge in more detail. The framework allows a modular design of knowledge representation and facilitates the creation of a more complex structure for modelling and reasoning.
The experiments conducted in this thesis show that the proposed framework is effective and useful for deriving inferences from input data, solving certain classification problems, and for prediction and decision-making.
7
DASH, Achyutananda. "KĀRAKA-TEHORY FOR KNOWLEDGE REPRESENTATION." 名古屋大学印度哲学研究室 (Department of Indian Philosophy, University of Nagoya), 1992. http://hdl.handle.net/2237/19175.
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8
Sukkarieh, Jana Zuheir. "Natural language for knowledge representation." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620452.
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9
何淑瑩 and Shuk-ying Ho. "Knowledge representation with genetic algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31222638.
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10
Kachintseva, Dina (Dina D. ). "Semantic knowledge representation and analysis." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/76983.
Повний текст джерелаАнотація:
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 103).<br>Natural language is the means through which humans convey meaning to each other - each word or phrase is a label, or name, for an internal representation of a concept. This internal representation is built up from repeated exposure to particular examples, or instances, of a concept. The way in which we learn that a particular entity in our environment is a "bird" comes from seeing countless examples of different kinds of birds. and combining these experiences to form a menial representation of the concept. Consequently, each individual's understanding of a concept is slightly different, depending on their experiences. A person living in a place where the predominant types of birds are ostriches and emus will have a different representation birds than a person who predominantly sees penguins, even if the two people speak the same language. This thesis presents a semantic knowledge representation that incorporates this fuzziness and context-dependence of concepts. In particular, this thesis provides several algorithms for learning the meaning behind text by using a dataset of experiences to build up an internal representation of the underlying concepts. Furthermore, several methods are proposed for learning new concepts by discovering patterns in the dataset and using them to compile representations for unnamed ideas. Essentially, these methods learn new concepts without knowing the particular label - or word - used to refer to them. Words are not the only way in which experiences can be described - numbers can often communicate a situation more precisely than words. In fact, many qualitative concepts can be characterized using a set of numeric values. For instance, the qualitative concepts of "young" or "strong" can be characterized using a range of ages or strengths that are equally context-specific and fuzzy. A young adult corresponds to a different range of ages from a young child or a young puppy. By examining the sorts of numeric values that are associated with a particular word in a given context, a person can build up an understanding of the concept. This thesis presents algorithms that use a combination of qualitative and numeric data to learn the meanings of concepts. Ultimately, this thesis demonstrates that this combination of qualitative and quantitative data enables more accurate and precise learning of concepts.<br>by Dina Kachintseva.<br>M.Eng.
11
Field, Robert Cushman. "Knowledge representation for contructed facilities." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/45479.
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Ho, Shuk-ying. "Knowledge representation with genetic algorithms /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22030256.
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13
Longo, Cristiano. "Set theory for knowledge representation." Doctoral thesis, Università di Catania, 2012. http://hdl.handle.net/10761/1031.
Повний текст джерелаАнотація:
The decision problem in set theory has been intensively
investigated in the last decades, and decision procedures
or proofs of undecidability have been provided for several
quantified and unquantified fragments of set theory.
In this thesis we study the decision problem for three novel
quantified fragments of set theory, which allow the explicit manipulation
of ordered pairs.
We present a decision procedure for each
language of this family, and prove that all of these procedures are optimal (in the sense that they run
in nondeterministic polynomial-time) when restricted to formulae with quantifier
nesting bounded by a constant.
The expressive power of
languages of this family is then measured in terms of set-theoretical
constructs they allow to express. In addition, these languages can
be profitably employed in knowledge representation,
since they allow to express a large amount description logic
constructs.
14
Schmidt, Daniel P. "Identifying Knowledge Gaps Using a Graph-based Knowledge Representation." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1588866076446257.
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15
Plate, Tony A. "Holographic reduced representation : distributed representation for cognitive structures /." Stanford, Calif. : CSLI, 2003. http://www.loc.gov/catdir/toc/uchi051/2003043513.html.
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16
Rubin, Eran. "Domain knowledge representation in information systems." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/15229.
Повний текст джерелаАнотація:
Information Systems and software embed knowledge about the domain in which they
operate. This knowledge can be very useful to various stakeholders in the organization,
including developers, users, and other organizational workers. However, it is not readily accessible and usually intertwined with implementation details. Making this knowledge available would be beneficial for several reasons. In particular: 1) software often needs to be updated to reflect changes in the organization; this causes the embedded knowledge to stay current; 2) the actual system development process often incorporates the use of methods and techniques to properly record domain knowledge; 3) knowledge embedded in
software is already available in a digital format; and 4) the tools typically used to manage system development (e.g. source and version controls) can be effective in management and control of knowledge. However, despite all these potential advantages, embedded knowledge is usually not readily accessible to knowledge seekers in the organization. This situation impedes the possible utilization of software-embedded knowledge. The objective of this dissertation is to develop ways of making software-embedded domain knowledge available, accessible, and usable to organizational users. The research challenge
is to identify what domain knowledge is involved in systems development, to find ways to formalize it, and to demonstrate that it can be explicitly represented in developed systems. The research covers three main aspects: 1) identifying and formalizing embedded domain knowledge obtained in systems development processes; 2) developing methods for representing this knowledge formally to facilitate its use during and after system development and, 3) demonstrate how this knowledge can be explicitly represented in the final IS implementation code. The first aspect, namely the nature of embedded knowledge, is addressed by analyzing the requirements engineering, systems analysis, and enterprise modeling literature in order to identify the main constructs used for domain representation. Formalization is then accomplished using ontological analysis. The feasibility of explicit representation is attained by suggesting a Model Driven Architectures (MDA) where the formalized knowledge is used to drive processing in the system.
Usability and usefulness of the ideas are demonstrated in two ways. First, case studies and examples show how domain knowledge acquired during extant methods of systems analysis can be represented using the proposed representation constructs. Second, a sample system design, supporting explicit domain knowledge representation in system code, is proposed and demonstrated via a simple prototype.
17
Sylvester, Igor Andrade. "A hierarchical systems knowledge representation framework." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41675.
Повний текст джерелаАнотація:
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>Includes bibliographical references (p. 57-58).<br>We present the design and implementation of a framework for storing and analysing knowledge about engineering systems. The hierarchical entity-relation-attribute model is useful for large data sets, in which it can abstract details so that human users are able to reason about the data. The time-series extension to the model abstracts temporal details. Finally, the implementation of the model includes an execution engine that can simulate the model in one time-slice or as a function of time.<br>by Igor Andrade Sylvester.<br>M.Eng.
18
Baring-Gould, Sengan. "SemNet : the knowledge representation of LOLITA." Thesis, Durham University, 2000. http://etheses.dur.ac.uk/4284/.
Повний текст джерелаАнотація:
Many systems of Knowledge Representation exist, but none were designed specifically for general purpose large scale natural language processing. This thesis introduces a set of metrics to evaluate the suitability of representations for this purpose, derived from an analysis of the problems such processing introduces. These metrics address three broad categories of question: Is the representation sufficiently expressive to perform its task? What implications has its design on the architecture of the system using it? What inefficiencies are intrinsic to its design? An evaluation of existing Knowledge Representation systems reveals that none of them satisfies the needs of general purpose large scale natural language processing. To remedy this lack, this thesis develops a new representation: SemNet. SemNet benefits not only from the detailed requirements analysis but also from insights gained from its use as the core representation of the large scale general purpose system LOLITA (Large-scale Object-based Linguistic Interactor, Translator, and Analyser). The mapping process between Natural language and representation is presented in detail, showing that the representation achieves its goals in practice.
19
Golden, Keith. "Planning and knowledge representation for softbots /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/6859.
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20
Pivkina, Inna Valentinovna. "REVISION PROGRAMMING: A KNOWLEDGE REPRESENTATION FORMALISM." Lexington, Ky. : [University of Kentucky Libraries], 2001. http://lib.uky.edu/ETD/ukycosc2001d00022/pivkina.pdf.
Повний текст джерелаАнотація:
Thesis (Ph. D.)--University of Kentucky, 2001.<br>Title from document title page. Document formatted into pages; contains vii, 121 p. : ill. Includes abstract. Includes bibliographical references (p. 116-119).
21
Corner, Robert J. "Knowledge representation in geographic information systems." Thesis, Curtin University, 1999. http://hdl.handle.net/20.500.11937/928.
Повний текст джерелаАнотація:
In order to satisfy increasing demand for better, smarter, more flexible land resource information an alternative form of representation is proposed. That representation is to be achieved through the coupling of Expert System methods and Geographic Information Systems. Instead of representing resource information using entities such as soil types, defined by rigid boundaries on a map, a more fluid presentation is proposed. Individual resource attributes will be represented by surfaces that describe their probability of occurrence, at a number of levels, across a landscape. Such flexible representations, which are designed to better capture the mental models behind their creation, are capable of being combined and synthesised to answer a wide range of resource queries.An investigation of methods of knowledge representation in a number of fields of research, led to the belief that a Bayesian Network provides a representational calculus that is appropriate to the "fuzzy" and imprecise conceptual models used in resource assessment. The fundamental mathematical principles of such networks have been tailored to provide a representation that is in tune with the intuitive processes of a surveyor's thinking.Software has been written to demonstrate the method and tested on a variety of data sets from Australia and overseas. These tests and demonstrations have used a range of densities of knowledge and range of acuity in evidential data. In general the results accord with the mental models used as drivers. A number of operational facets of the method have been highlighted during these demonstrations and attention has been given to a discussion of them.
22
Corner, Robert J. "Knowledge representation in geographic information systems." Curtin University of Technology, School of Spatial Sciences, 1999. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=11740.
Повний текст джерелаАнотація:
In order to satisfy increasing demand for better, smarter, more flexible land resource information an alternative form of representation is proposed. That representation is to be achieved through the coupling of Expert System methods and Geographic Information Systems. Instead of representing resource information using entities such as soil types, defined by rigid boundaries on a map, a more fluid presentation is proposed. Individual resource attributes will be represented by surfaces that describe their probability of occurrence, at a number of levels, across a landscape. Such flexible representations, which are designed to better capture the mental models behind their creation, are capable of being combined and synthesised to answer a wide range of resource queries.An investigation of methods of knowledge representation in a number of fields of research, led to the belief that a Bayesian Network provides a representational calculus that is appropriate to the "fuzzy" and imprecise conceptual models used in resource assessment. The fundamental mathematical principles of such networks have been tailored to provide a representation that is in tune with the intuitive processes of a surveyor's thinking.Software has been written to demonstrate the method and tested on a variety of data sets from Australia and overseas. These tests and demonstrations have used a range of densities of knowledge and range of acuity in evidential data. In general the results accord with the mental models used as drivers. A number of operational facets of the method have been highlighted during these demonstrations and attention has been given to a discussion of them.
23
Hope, Kristin Lofthus. "New Knowledge Objects? Exploring Cultures of Representation in Knowledge-Intensive Work." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Arts, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1728.
Повний текст джерела
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Wong, Gladys Magali. "Depiction and domains in visual knowledge representation." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/26207.
Повний текст джерелаАнотація:
Systems need knowledge to behave intelligently in a complex environment. This thesis presents a formalism for characterizing the knowledge in a world while providing a framework that can be utilzed efficiently in computation. Thus Domain Theory is developed as a knowledge representation scheme.
Under Domain Theory, the knowledge in a world is divided into domains that are interrelated through the relation of representation. This theory is evaluated as appropriate for knowledge representation using descriptive and procedural adequacy criteria.
Domain Theory is applied to produce a working system called Depicts. Depicts is written in Prolog which is well suited for implementing Domain Theory. Given a graphical representation, Depicts returns a relational description and, conversely, given a relational description, Depicts returns a graphical representation.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate
25
Vybihal, Joseph. "Search and knowledge representation in analogical reasoning." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61766.
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26
Salgado-Arteaga, Francisco. "A study on object-oriented knowledge representation." Virtual Press, 1995. http://liblink.bsu.edu/uhtbin/catkey/935944.
Повний текст джерелаАнотація:
This thesis is a study on object-oriented knowledge representation. The study defines the main concepts of the object model. It also shows pragmatically the use of object-oriented methodology in the development of a concrete software system designed as the solution to a specific problem.The problem is to simulate the interaction between several animals and various other objects that exist in a room. The proposed solution is an artificial intelligence (Al) program designed according to the object-oriented model, which closely simulates objects in the problem domain. The AI program is conceived as an inference engine that maps together a given knowledge base with a database. The solution is based conceptually on the five major elements of the model, namely abstraction, encapsulation, modularity, hierarchy, and polymorphism.The study introduces a notation of class diagrams and frames to capture the essential characteristics of the system defined by analysis and design. The solution to the problem allows the application of any object-oriented programming language. Common Lisp Object System (CLOS) is the language used for the implementation of the software system included in the appendix.<br>Department of Computer Science
27
Hong, Xin. "Heuristic knowledge representation and evidence combination parallelization." Thesis, University of Ulster, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365938.
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28
Nowbati, Behzad. "Visual information and knowledge representation in organisations." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/8467.
Повний текст джерелаАнотація:
The construction industry's environment is continually changing. Employees are now more geographically widespread and diverse, both culturally and educationally, than ever before. A great deal of research has been carried out on knowledge acquisition and storage, but there is still a distinct lack of research into knowledge presentation and communication. Information and knowledge presentation play a significant role in daily decision-making processes, when inappropriate decisions may result from inaccurate or poorly communicated information. The simplified, filtered coherent presentation of explicit knowledge can be instrumental to a successful, profitable and safety conscious business. Wates Construction is a major construction company and employs around 1300 people directly, as well as various subcontractors on different projects. Their current turn over is around £1billion, they are based in the UK and have branches in Ireland and Abu Dhabi. Wates realised their existing information system was inefficiently conveying information to its employees and the need to provide a simplified system, to assist staff's decision-making processes. Earlier IT professionals' attempts to make the system more usable had made no significant difference to its performance.
29
Smith, Julian P. "Neural networks, information theory and knowledge representation." Thesis, University of Edinburgh, 1996. http://hdl.handle.net/1842/20801.
Повний текст джерела
30
Perini, Laura Therese. "Visual representations and scientific knowledge /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC IP addresses, 2002. http://wwwlib.umi.com/cr/ucsd/fullcit?p3036945.
Повний текст джерела
31
Ramos, González Juan José. "PML - A modeling Language for Physical Knowledge Representation." Doctoral thesis, Universitat Autònoma de Barcelona, 2003. http://hdl.handle.net/10803/5801.
Повний текст джерелаАнотація:
Esta tesis versa sobre la automatización del proceso de modelado de sistemas físicos. La automatización del modelado ha sido el objetivo común en la mayor parte de las principales herramientas disponibles hoy en día. La reutilización de modelos es probablemente el principal enfoque adoptado por dichas herramientas con el objeto de reducir el coste asociado a la tarea de modelado. No obtante, permitir la reutilización de modelos predefinidos no es una cuestión trivial y, como se discute con profucdidad en la tesis, la reutilización de modelos no puede ser garantizada cuando han sido predefinidos para representar la dinámica del sistima en un contextor físico concreto. Con el fin de evitar las restricciones sobre la reutilización derivadas de la formylación matemática de las dinámicas de interés, el lenguaje de modelado debe establecer un clara separación entre los aspectos relacionados con la representación del comportamiento físico (conocimiento declarativo) y los aspectos matemáticos relacionados con las herramientas de simulación (conocimiento procedural). El conomiento declarativo representará el comportamiento físico y será utilizado para analizar el contexto físico de reutilización de los modelos con el objeto de establecer la formulación adecuada de las dinámicas de interés. <br/>El propósito de este trabajo ha sido el diseño de un lenguaje de modelado, PML, capaz de automatizar el proceso de modelado asegurando la reusabilidad de modelos que pueden ser predefinidos de manera independiente al contexto físico don seran reutilizados. La reutilización de modelos se contempla tanto en la contrucción de nuevos modelos (modelado estructurado) como en su utilización para diferentes objetivos de experimentación. Los nuevos modelos son contruidos acoplando modelos predefinidos de acurdo a la topología física del sistema modelado. Tales modelos pueden ser manipulados para adecuarlos a distintos objetivos de experimentación, adecuándose la formulación matemática de la dinámicas de interés marcadas por dichos objetivos.<br/>PML es un lenguaje de modelado orientado a objetos diseñado para describir el comportamiento del sistema físico mediante estructuras de representación modulares (clases de modelado). La clases PML representan conceptos físicos que son familiares al modelador. El conocimiento físico declarado por la clases se utiliza para analizar los modelos estructurados, obteniéndose de manera automatizada la representación matemática de las dinámicas de interés.<br>The topic of this thesis is the automated modeling of physical systems. Modeling automation has been a common objective in many of the present modeling tools. Reuse of predefined models is probably the main approach adopted by many of them in order to reduce the modeling burden. However, to facilitate reuse is difficult to achieve and, as it is discussed thoroughly in the thesis, reusability of models can not be assured when they are predefined to represent the system dynamics in a particular physical context. In order to avoid the reuse constraints due to the system dynamics formulation, a modeling language should be defined with a clear separation between the physical behaviour representation aspects (declarative physical knowledge) and the computational aspects concerning to model simulation (procedural computational knowledge). The physical knowledge will represent the system behaviour and it will support the analysis of the model reusing context in order to set the system dynamics formulation. <br/>The aim of this work is the design of a modeling language, PML, able to automate the modeling process by assuring the reusability of ready-made models independently of the physical context where they have been defined. The reuse of a predefined model contemplates both the construction of new models (structured modeling) and the model usage for different experimentation purposes. New models are constructed by coupling predefined models according to the physical system topology. Such structured models are manipulated in order to obtain the representation of the system dynamics which are of interest for the experimentation purposes.<br/>PML is an object oriented modeling language designed to represent system behaviour by means of modular structures (modeling classes). The PML modeling classes describe physical concepts well-known by the modeller. The physical knowledge declared by the modeling classes is used to analyze structured models in order to generate automatically the mathematical representation of the system dynamics. The simulation model is obtained by means of an equation-based object oriented modeling language.
32
Suzic, Robert. "Knowledge representation and stocastic multi-agent plan recognition." Licentiate thesis, KTH, Numerical Analysis and Computer Science, NADA, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-314.
Повний текст джерелаАнотація:
<p>To incorporate new technical advances into military domain and make those processes more <i>efficient</i> in accuracy, time and cost, a new concept of Network Centric Warfare has been introduced in the US military forces. In Sweden a similar concept has been studied under the name Network Based Defence (NBD). Here we present one of the methodologies, called tactical plan recognition that is aimed to support NBD in future.</p><p>Advances in sensor technology and modelling produce large sets of data for decision makers. To achieve <i>decision superiority</i>, decision makers have to act agile with proper, adequate and relevant information (data aggregates) available. Information fusion is a process aimed to support decision makers’ situation awareness. This involves a process of combining data and information from disparate sources with <i>prior</i> information or knowledge to obtain an improved state estimate about an agent or phenomena. <i>Plan recognition</i> is the term given to the process of inferring an agent’s intentions from a set of actions and is intended to support decision making.</p><p>The aim of this work has been to introduce a methodology where prior (empirical) knowledge (e.g. behaviour, environment and organization) is represented and combined with sensor data to recognize plans/behaviours of an agent or group of agents. We call this methodology <i>multi-agent plan recognition</i>. It includes knowledge representation as well as imprecise and statistical inference issues.</p><p>Successful plan recognition in large scale systems is heavily dependent on the data that is supplied. Therefore we introduce a <i>bridge</i> between the plan recognition and sensor management where results of our plan recognition are reused to the control of, give <i>focus of attention</i> to, the sensors that are supposed to acquire most important/<i>relevant</i> information.</p><p>Here we combine different theoretical methods (Bayesian Networks, Unified Modeling Language and Plan Recognition) and apply them for tactical military situations for ground forces. The results achieved from several proof-ofconcept models show that it is possible to model and recognize behaviour of tank units.</p>
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Jordon, Lester Arlington. "Automating knowledge acquisition and representation with fuzzy logic." Thesis, University of British Columbia, 1991. http://hdl.handle.net/2429/29990.
Повний текст джерелаАнотація:
An interactive computer program has been developed to automate the construction of knowledge bases in expert system development. The program incorporates many user friendly features which allow users who may not understand the concepts of fuzzy logic or the complexity of the knowledge acquisition process to develop useful and complete Expert Systems.
Expert systems formalism are being successfully used in the industry. A major bottleneck in development of these systems lies in the knowledge acquisition phase. This study presents an induction system, based on fuzzy logic, which successfully automates the knowledge acquisitions process when the domain knowledge is embodied within discrete numerical data.
A tabloid database representing some desired input/output relationship is input to the system. Fuzzy expressions such as "high", "low" or "large" are either created automatically by the system or described explicitly by the user. These fuzzy expressions are automatically associated into an accurate and minimum rule set which models the desired input/output relationship.
The system was tested on the development of a knowledge base for a secondary crusher controller and a second more complex non-monotonic input/output relationship. In the controller example the knowledge bases developed were simpler, more accurate and built much faster than using a traditional interview approach. The non-monotonic relationship was also accurately described by a simple knowledge base.<br>Applied Science, Faculty of<br>Mining Engineering, Keevil Institute of<br>Graduate
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Saund, Eric. "The Role of Knowledge in Visual Shape Representation." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/6833.
Повний текст джерелаАнотація:
This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.
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Suzić, Robert. "Knowledge representation and stochastic multi-agent plan recognition /." Stockholm, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-314.
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Tabaeh, Izadi Masoumeh. "On knowledge representation and decision making under uncertainty." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103012.
Повний текст джерелаАнотація:
Designing systems with the ability to make optimal decisions under uncertainty is one of the goals of artificial intelligence. However, in many applications the design of optimal planners is complicated due to imprecise inputs and uncertain outputs resulting from stochastic dynamics. Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical framework to model these kinds of problems. However, the high computational demand of solution methods for POMDPs is a drawback for applying them in practice.<br>In this thesis, we present a two-fold approach for improving the tractability of POMDP planning. First, we focus on designing good heuristics for POMDP approximation algorithms. We aim to scale up the efficiency of a class of POMDP approximations called point-based planning methods by designing a good planning space. We study the effect of three properties of reachable belief state points that may influence the performance of point-based approximation methods. Second, we investigate approaches to designing good controllers using an alternative representation of systems with partial observability called Predictive State Representation (PSR). This part of the thesis advocates the usefulness and practicality of PSRs in planning under uncertainty. We also attempt to move some useful characteristics of the PSR model, which has a predictive view of the world, to the POMDP model, which has a probabilistic view of the hidden states of the world. We propose a planning algorithm motivated by the connections between the two models.
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Stephens, Robert Andrew. "Representation and knowledge acquisition : the problem of language." Thesis, University of the West of England, Bristol, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321831.
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Sharif, Amir M. "Knowledge representation within information systems in manufacturing environments." Thesis, Brunel University, 2004. http://bura.brunel.ac.uk/handle/2438/2455.
Повний текст джерелаАнотація:
Representing knowledge as information content alone is insufficient in providing us with an understanding of the world around us. A combination of context as well as reasoning of the information content is fundamental to representing knowledge in an information system. Knowledge Representation is typically concerned with providing structures and theories that are used as a basis for intelligent reasoning. For this research however, the author defines an alternative meaning, which is related to how knowledge is used in a given context. Thus, this dissertation provides a contribution to the field of knowledge within information systems, in terms of the development of a frame-of-reference that will support the reader in navigating through the different forms of explicit and tacit knowledge use within the manufacturing industry. In doing so, the dissertation also presents the generation of a novel classification of three forms of knowledge (Structural, Interpretive and Evaluative forms); the development of a conceptual framework which highlights the drivers for knowledge transformation; and the development of a conceptual model which seeks to envelop both the content as well as the context of knowledge (Semiotic as well as Symbiotic factors). This is established through the use of an Empirical, Quantitative case study approach, that seeks to explore an interpretivist view of knowledge representation within two information systems contexts, within two UK manufacturing organisations. The first case study presents how a-priori knowledge assumptions are used in a computer aided engineering decision-making task within a high technology manufacturing company. The second case study shows how knowledge is used within the IT/IS investment evaluation decision making process, within a manufacturing SME. In doing so, both case studies attempt to elucidate the inherent, underlying relationship between explicit and tacit knowledge, via a frame-of-reference developed by the author which defines key drivers for knowledge transformation.
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Jackson, Thomas Oliver. "Frame based knowledge representation in an ADAM architecture." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261081.
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Brook, Katherine Eliza. "Proust and the avant-garde : perception, knowledge, representation." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/proust-and-the-avantgarde(43662227-f55c-493d-957c-13d5c9b68ef2).html.
Повний текст джерелаАнотація:
This thesis compares Proust’s Recherche with the work of the Cubists, Futurists, and Surrealists. Few scholars have considered the novel’s engagement with avant-garde ideas and aesthetics, despite Proust’s geographical and temporal proximity to avant-garde activity. Without arguing extensively for direct influence or even significant interaction between the two, my research focuses on a broader pool of ideas and cultural-historical developments, around which Proust’s work can be brought into dialogue with both the collective aims of particular groups within the avant-garde, and with the paintings and (to a lesser extent) writings of individual artists. Throughout the thesis, I use their work as a means of shedding light on the conflict and crossover between states of ‘insidership’ and ‘outsidership’, and on the manner in which these states define relations between perceiving, acting subjects and the external objects and spaces they encounter. Chapter 1 focuses on the artistic perceptive faculty and the relation it enables between the artist and the external world, using Bergson’s opposition of ‘analysis’ and ‘intuition’ as a theoretical framework. Chapter 2 is centred around the metaphor of the work of art as a ‘window on the world’ and its implication that a painting is primarily a representation, rather than an object in its own right. Chapter 3 investigates the influence of mechanised transport technologies both on perceptions of space and on relations between people, while Chapter 4 uses Didier Anzieu’s theory of the Moi-peau to argue that the self is defined not only by bodily but by architectural boundaries, which also shape the subject’s relationships with other people. Ultimately, the thesis asks whether the work of Proust and the avant-gardes conceives of the subject’s interaction with the world as a function of surface or of depth, or as a more complex troubling between the two.
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Patel, Mukesh Jayantilal. "Human text processing and models of knowledge representation." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/30632.
Повний текст джерелаАнотація:
Two experimental studies on human text processing and knowledge representation are reported. They are designed to explore the nature of cognitive processes in working memory and long term representations associated with the resolution of reference in texts. Resolution of references occurs when properties of distinct individuals are bound together in memory. Stenning, Shepherd and Levy (1988) propose that binding is achieved by recruiting existing general knowledge associations based on the semantic structure of texts. They present models of representation structures in a novel Memory for Individual Task (MIT), and show that these models can explain certain patterns of retrieval error frequencies. A statistical model of construction of representation processes which account for a particular pattern of reading times in terms of key aspects of the structure of MIT texts is also presented. The reading times results of the first MIT experiment, in which the order of switches in reference between individuals is unpredictable, is presented together with as extended construction processing model which capture phenomena of reference changes. The new models show that unpredictable reference changes cost time as a function of the complexity of the individual to which reference is switched, without disrupting the modular account of processing centred on referenced individual reported by Stenning, Shepherd and Levy (1988). Analysis of recall errors reveal an effect of presentation order, which results in confusion over identity of individuals' properties, providing a basis for a distinction between 'primary' and 'secondary' individual, each requiring different syllabic rehearsal processing. These working memory processes are incorporated in a model which reveals interaction between rehearsal and semantic processes. The error data is further analysed with respect to logically constraining solutions to representations of bindings with 'direct' and 'indirect' structures. Direct systems represent binding by structural devices referring to individual identities in their representation; indirect systems represent binding only through quantificational facts. Both direct and indirect models are developed and the latter one shown to be at least as good a fit to the data as the former, which suggests that solution to the binding problem is represented in a distributed manner closer to PDP systems. Much of the theoretical underpinning of the findings of the first study, is dependent on aspects of the semantic structures which reflect regularities in the temporal order of descriptions of individuals in MIT texts. The second study investigates the extent to which such regularities facilitated the sorts of structures constructed in representations of solutions to the binding problem, and interaction between temporal order of presentation and working memory processes. Analyses of reading times show that, while order of presentation of properties has no significant effect on working memory processes, differences in availability of information about higher level semantic structure does require extra processing. A statistical model which factors out some of this processing load as due to specific changes in the semantic structure of MIT texts is presented.
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Oshurko, Ievgeniia. "Knowledge representation and curation in hierarchies of graphs." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN024.
Повний текст джерелаАнотація:
L'extraction automatique des intuitions et la construction de modèles computationnels à partir de connaissances sur des systèmes complexes repose largement sur le choix d'une représentation appropriée. Ce travail s'efforce de construire un cadre adapté pour la représentation de connaissances fragmentées sur des systèmes complexes et sa curation semi-automatisé.Un système de représentation des connaissances basé sur des hiérarchies de graphes liés à l'aide d'homomorphismes est proposé. Les graphes individuels représentent des fragments de connaissances distincts et les homomorphismes permettent de relier ces fragments. Nous nous concentrons sur la conception de mécanismes mathématiques,basés sur des approches algébriques de la réécriture de graphes, pour la transformation de graphes individuels dans des hiérarchies qui maintient des relations cohérentes entre eux.De tels mécanismes fournissent une piste d'audit transparente, ainsi qu'une infrastructure pour maintenir plusieurs versions des connaissances.La théorie développée est appliquée à la conception des schémas pour les bases de données orientée graphe qui fournissent des capacités de co-évolution schémas-données.Ensuite, cette théorie est utilisée dans la construction du cadre KAMI, qui permet la curation des connaissances sur la signalisation dans les cellules. KAMI propose des mécanismes pour une agrégation semi-automatisée de faits individuels sur les interactions protéine-protéine en corpus de connaissances, la réutilisation de ces connaissances pour l'instanciation de modèles de signalisation dans différents contextes cellulaires et la génération de modèles exécutables basés sur des règles<br>The task of automatically extracting insights or building computational models fromknowledge on complex systems greatly relies on the choice of appropriate representation.This work makes an effort towards building a framework suitable for representation offragmented knowledge on complex systems and its semi-automated curation---continuouscollation, integration, annotation and revision.We propose a knowledge representation system based on hierarchies of graphs relatedwith graph homomorphisms. Individual graphs situated in such hierarchies representdistinct fragments of knowledge and the homomorphisms allow relating these fragments.Their graphical structure can be used efficiently to express entities and their relations. Wefocus on the design of mathematical mechanisms, based on algebraic approaches to graphrewriting, for transformation of individual graphs in hierarchies that maintain consistentrelations between them. Such mechanisms provide a transparent audit trail, as well as aninfrastructure for maintaining multiple versions of knowledge.We describe how the developed theory can be used for building schema-aware graphdatabases that provide schema-data co-evolution capabilities. The proposed knowledgerepresentation framework is used to build the KAMI (Knowledge Aggregation and ModelInstantiation) framework for curation of cellular signalling knowledge. The frameworkallows for semi-automated aggregation of individual facts on protein-protein interactionsinto knowledge corpora, reuse of this knowledge for instantiation of signalling models indifferent cellular contexts and generation of executable rule-based models
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Nikiforou, Savvas. "Selection of Clinical Trials: Knowledge Representation and Acquisition." Scholar Commons, 2002. https://scholarcommons.usf.edu/etd/1527.
Повний текст джерелаАнотація:
When medical researchers test a new treatment procedure, they recruit patients with appropriate health problems and medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves matching of medical records with a list of eligibility criteria.
A recent project at the University of South Florida has been aimed at the automation of this task. The project has involved the development of an expert system that selects matching clinical trials for each patient. If a patient's data are not sufficient for choosing a trial, the system suggests additional medical tests.
We report the work on the representation and entry of the related selection criteria and medical tests. We first explain the structureof the system's knowledge base, which describes clinical trials and criteria for selecting patients. We then present an interface that enables a clinician to add new trials and selection criteria without the help of a programmer. Experiments show that the addition of a new clinical trial takes ten to twenty minutes, and that novice users learn the full functionality of the interface in about an hour.
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Chenu-Abente, Acosta Ronald. "Knowledge and Artifact Representation in the Scientific Lifecycle." Doctoral thesis, Università degli studi di Trento, 2012. https://hdl.handle.net/11572/368068.
Повний текст джерелаАнотація:
This thesis introduces SKOs (Scientific Knowledge Object) a specification for capturing the knowledge and artifacts that are produced by the scientific research processes. Aiming to address the current existing limitations of scientific production this specification is focused on reducing the work overhead of scientific creation, being composable and reusable, allow continuous evolution and facilitate collaboration and discovery among researchers. To do so it introduces four layers that capture different aspects of the scientific knowledge: content, meaning, ordering and visualization.
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Chenu-Abente, Acosta Ronald. "Knowledge and Artifact Representation in the Scientific Lifecycle." Doctoral thesis, University of Trento, 2012. http://eprints-phd.biblio.unitn.it/713/1/Kw_and_Artifact_Representation_in_the_Scientific_Lifecycle_.pdf.
Повний текст джерелаАнотація:
This thesis introduces SKOs (Scientific Knowledge Object) a specification for capturing the knowledge and artifacts that are produced by the scientific research processes. Aiming to address the current existing limitations of scientific production this specification is focused on reducing the work overhead of scientific creation, being composable and reusable, allow continuous evolution and facilitate collaboration and discovery among researchers. To do so it introduces four layers that capture different aspects of the scientific knowledge: content, meaning, ordering and visualization.
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Bhuyan, Bikram Pratim. "Neuro-symbolic knowledge hypergraphs : knowledge representation and learning in neuro-symbolic artificial intelligence." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG024.
Повний текст джерелаАнотація:
L'intégration du raisonnement symbolique et de l'apprentissage neuronal en Intelligence Artificielle (IA) est devenue de plus en plus cruciale à mesure que la demande de modèles capables de gérer des données complexes, dynamiques et interconnectées croît. Alors que les approches traditionnelles ont fait des progrès dans ces domaines séparément, un cadre unifié combinant ces paradigmes est essentiel pour faire progresser la capacité de l'IA à interpréter, apprendre et prédire dans des environnements réels.Malgré les avancées des modèles symboliques et neuronaux, la littérature existante révèle un manque de cadres qui intègrent efficacement les deux, en particulier dans le contexte de la représentation et de l'apprentissage des connaissances spatio-temporelles. Les graphes de connaissances traditionnels (KGs), bien qu'utiles, peinent à capturer les relations d'ordre supérieur et les changements dynamiques et temporels. Cette limitation nécessite une nouvelle approche capable d'intégrer une logique d'ordre supérieur et une structure flexible pour modéliser les complexités du monde réel.L'objectif de cette étude est de développer et de valider un cadre d'Hypergraphe de Connaissances Neuro-Symboliques qui étend les graphes de connaissances traditionnels en Graphes de Connaissances d'Ordre Supérieur (HOKGs), capables de représenter des relations n-aires et temporelles. Le cadre intègre la Logique Temporelle du Second Ordre Monadique (MSOTL) pour le raisonnement temporel et les Réseaux Neuronaux d'Hypergraphes (HGNNs) pour l'apprentissage et la modélisation prédictive, reliant ainsi les paradigmes symboliques et neuronaux.La méthodologie consiste à formuler une structure d'hypergraphe robuste qui encode des relations spatio-temporelles et sémantiques en utilisant la MSOTL. Celle-ci est ensuite couplée aux réseaux neuronaux d'hypergraphes, intégrant des mécanismes de convolution et d'attention pour un apprentissage et une inférence efficaces. Le cadre est testé sur des scénarios réels, en particulier dans l'agriculture urbaine, pour démontrer ses capacités prédictives et sa robustesse.Les résultats clés montrent que le cadre proposé améliore significativement la capacité d'expression et d'inférence par rapport aux KGs traditionnels. La composante MSOTL permet une modélisation précise des relations temporelles et spatiales, tandis que les HGNNs valident l'exactitude prédictive. L'étude de cas sur l'agriculture urbaine met en évidence l'utilité du cadre, démontrant comment il peut fournir des informations significatives et des prédictions précises sur les pratiques agricoles dynamiques.Cette recherche a de vastes implications pour les applications de l'IA nécessitant une représentation des connaissances complexes et dynamiques, telles que les villes intelligentes, la surveillance environnementale, et au-delà. L'approche proposée, basée sur l'hypergraphe, ouvre la voie à l'intégration de logiques d'ordre supérieur, de connaissances basées sur l'ontologie et de l'apprentissage profond, offrant une solution globale aux limites observées dans les graphes de connaissances actuels et les modèles d'IA<br>The integration of symbolic reasoning and neural learning in Artificial Intelligence (AI) has become increasingly important as the demand for models capable of handling complex, dynamic, and interconnected data grows. While traditional approaches have made progress in these domains separately, a unified framework that combines these paradigms is crucial for advancing AI's ability to interpret, learn, and predict in real-world environments.Despite the advancements in symbolic and neural models, existing literature reveals a gap in frameworks that effectively merge the two, particularly in the context of spatio-temporal knowledge representation and learning. Traditional knowledge graphs (KGs), though useful, struggle with capturing high-order relationships and dynamic, temporal changes. This limitation necessitates a novel approach that can incorporate higher-order logic and flexible structure to model real-world complexities.The objective of this study is to develop and validate a Neuro-Symbolic Knowledge Hypergraph framework that extends traditional knowledge graphs into Higher-Ordered Knowledge Graphs (HOKGs) capable of representing n-ary and temporal relationships. The framework integrates Monadic Second-Order Temporal Logic (MSOTL) for temporal reasoning and Hypergraph Neural Networks (HGNNs) for learning and predictive modeling, bridging the symbolic and neural paradigms.The methodology involves formulating a robust hypergraph structure that encodes spatio-temporal and semantic relationships using MSOTL. It is then coupled with hypergraph neural networks, incorporating convolution and attention mechanisms for effective learning and inference. The framework is tested on real-world scenarios, specifically in urban agriculture, to demonstrate its predictive capabilities and robustness.Key findings show that the proposed framework significantly enhances the expressiveness and inference capacity compared to traditional KGs. The MSOTL component ensures precise modeling of temporal and spatial relationships, while HGNNs validate predictive accuracy. The case study on urban agriculture highlights the framework's utility, showcasing how it can provide meaningful insights and precise predictions on dynamic agricultural practices.This research has broad implications for AI applications requiring complex, dynamic knowledge representation, such as smart cities, environmental monitoring, and beyond. The proposed hypergraph-based approach opens pathways for integrating higher-order logic, ontology-based knowledge, and deep learning, offering a comprehensive solution to the limitations observed in current knowledge graphs and AI models
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Shiri, Ali Asghar, and Crawford Revie. "Thesauri on the Web: Current developments and trends." MCB University press, 2000. http://hdl.handle.net/10150/105440.
Повний текст джерелаАнотація:
This article provides an overview of recent developments relating to the application of thesauri in information organisation and retrieval on the World Wide Web. It describes some recent thesaurus projects undertaken to facilitate resource description and discovery and access to wide-ranging information resources on the Internet. Types of thesauri available on the Web, thesauri integrated in databases and information retrieval systems, and multiple-thesaurus systems for cross-database searching are also discussed. Collective efforts and events in addressing the standardisation and novel applications of thesauri are briefly reviewed.
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Marshall, Byron, and Therani Madhusudan. "Element Matching in Concept Maps." ACM, 2004. http://hdl.handle.net/10150/105657.
Повний текст джерелаАнотація:
Artificial Intelligence Lab, Department of MIS, University of Arizona<br>Concept maps (CM) are informal, semantic, node-link conceptual graphs used to represent knowledge in a variety of applications. Algorithms that compare concept maps would be useful in supporting educational processes and in leveraging indexed digital collections of concept maps. Map comparison begins with element matching and faces computational challenges arising from vocabulary overlap, informality, and organizational variation. Our implementation of an adapted similarity flooding algorithm improves matching of CM knowledge elements over a simple string matching approach.
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Verbeek, Thomas. "The design of a model for the acquisition, reuse and creation of knowledge in a civil engineering environment." Thesis, University of Pretoria, 2018. http://hdl.handle.net/2263/64301.
Повний текст джерелаАнотація:
A model is designed for the restructuring of knowledge. By way of suitably designed ontologies knowledge can be analysed to facilitate the creation of new knowledge and to render the knowledge suitable for reuse and for linkage to word-wide ontologies.<br>SUMMARY
The need for this research emanated from the requirement for learning and adaptation in the fast-changing world we live in today. The changing world goes along with developments in communication means, whereby information becomes more accessible and sophisticated daily. A vast number of resources is available and accessible, distributing an enormous amount of information. The need is to turn these vast amounts of information into usable knowledge for use by an engineer in practice. Restructuring of knowledge is one way of approaching this need and is addressed in this study. This process can be facilitated by experienced persons who know what knowledge is needed in practice. There is a decline in the numbers of experienced civil engineers, leaving a gap between the supply and demand for suitably qualified and experienced civil engineers. The objective of this study is to meet the need for the restructuring of knowledge by the design a model (referred to as a logic base in this study) for the acquisition, reuse and the creation of engineering knowledge in a civil engineering environment.
The main research question posed in this study is as follows:
What are the key characteristics of a model (termed a “logic base” in this study) for the acquisition, reuse and the creation of knowledge in a civil engineering environment?
This research commences with a set of research questions, followed by a literature review. Consideration is given to theories of knowledge, various methods of knowledge creation and knowledge acquisition. Several problem-solving techniques are reviewed. The structuring and architecture of knowledge and ontologies are researched and the role of systems engineering is studied. Various research methods are investigated and it is shown that case study research is the most suitable for the development of ontologies in civil engineering. The ontology of the logic base is therefore based on typical topics of case studies. Concept maps are employed to structure knowledge. This is done by defining appropriate concepts and classifying these into several ontological levels. The relationships among concepts and other influencing domains are studied. Knowledge of these relationships enables the application of several problem-solving techniques that enhance and stimulate the creation of knowledge.
A logic base is designed containing three modules, namely an input module whereby concept maps are used to capture and structure knowledge entities. The second module consists of an analysis module where problem-solving can be done. The third module contains the output of work and processes where engineering knowledge can be documented for reuse.
The contribution of this research lies in the design of an application in knowledge management in the field of civil engineering. Integration is done of ontologies, knowledge theories, knowledge acquisition and knowledge creation through problem-solving techniques. Knowledge is structured that can be linked to other external civil engineering taxonomies and ontologies. This enhancement of knowledge makes knowledge explicit and renders it suitable for reuse. When engineers are equipped in the use of the logic base, problems can be addressed in a holistic way and the underlying thought processes can be documented. This may be of great value to inexperienced engineers and for the preservation of valuable knowledge.
Some case studies are analysed to demonstrate the functioning of the model.<br>Thesis (DPhil) University of Pretoria 2018.<br>Information Science<br>DPhil<br>Unrestricted
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Diab, Mohammed. "Knowledge representation and reasoning for perception-based manipulation planning." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/671505.
Повний текст джерелаАнотація:
This thesis develops a series of modeling and reasoning tools for knowledge-oriented manipulation planning in semi/unstructured environments. The main idea is to use high-level knowledge-based reasoning to capture a rich semantic description of the scene, knowledge about the physical behavior of the objects, and inference mechanism to reason about the potential manipulation actions. Moreover, a multi-model sensory module is proposed to perceive the objects in the environment and build the ontological knowledge.
The first part of the thesis is focused on the techniques to provide useful knowledge to guide and facilitate the planning process within a classical-based manipulation planning framework. This planning framework facilitates the combination of task and motion planning approaches which includes Fast Forward (FF), a classical symbolic planning approach to compute the sequence of actions to be done in a certain task, and physics-based motion planning which deals with motions and possible interactions with the objects. The tool proposed to provide useful knowledge to the planning process is called Perception and Manipulation Knowledge (PMK). It provides, on the one hand, a standardized formalization under several foundations, such as the Suggested Upper Merged Ontology (SUMO), and the Core Ontology for Robotics and Automation (CORA), in order to facilitate the shareability and reusability when the interaction between humans and/or robots is done. On the other hand, it provides the inference mechanism to reason about TAMP requirements, such as robot capabilities, action constraints, action feasibility, and manipulation behaviors. Moreover, PMK allows breaking the closed-world assumption of classical-based manipulation planning approaches. This proposal has been tested for a serving task in a table-top manipulation problem.<br>Esta tesis desarrolla una serie de herramientas de modelado y razonamiento para la planificación de la manipulación basada en el conocimiento en entornos no estructurados o semiestructurados. La idea principal es utilizar un razonamiento basado en el conocimiento de alto nivel para capturar una descripción semántica de la escena, conocimiento sobre el comportamiento físico de los objetos y un mecanismo de inferencia para razonar sobre las posibles acciones de manipulación. Además, se propone un módulo sensorial multimodelo para percibir los objetos del entorno y construir conocimiento ontológico. La primera parte de la tesis se centra en las técnicas para proporcionar conocimientos útiles para guiar y facilitar el proceso de planificación dentro de un marco de planificación de manipulación clásico. Este marco de planificación facilita la combinación de enfoques de planificación de tareas y movimientos (TAMP) que incluye Fast Forward (FF) que es un enfoque clásico de planificación simbólica para calcular la secuencia de acciones a realizar en una determinada tarea, y la planificación de movimiento basada en la física que trata con movimientos y posibles interacciones con los objetos. La herramienta propuesta para aportar conocimientos útiles al proceso de planificación se denomina Conocimiento de Percepción y Manipulación (PMK), la cual proporciona una formalización estandarizada bajo varios fundamentos, como la Ontología Superior Sugerida Sugerida (SUMO), y la Ontología Core para Robótica y Automatización (CORA), con el fin de facilitar la compartibilidad y reutilización cuando se produzca la interacción entre humanos y/o robots. La segunda parte de la tesis se centra en proporcionar conocimientos útiles para un enfoque de planificación basado en la lógica. Está particularizado para el ensamblaje, que tiene en cuenta lacciones de manipulación para acoplar/desacoplar o unir/separar objetos. Las secuencias de ensamblaje se pueden representar de forma elegante usando teorías de lógica descriptiva. Con tal secuencia, el robot puede descubrir el próximo paso en el ensamblaje a través de la inferencia lógica. Sin embargo, antes de realizar una acción, el robot debe asegurarse de que se cumplan varias restricciones espaciales, como que las partes que se van a unir sean accesibles, no ocluidas, etc. Tales inferencias son muy complicadas de respaldar en teorías lógicas, pero existen algoritmos especializados que calculan de manera eficiente relaciones cualitativas, como si un objeto es accesible. Aquí se propone un razonamiento heterogéneo que requiere la integración entre el nivel de planificación de ensamblajes basado en el conocimiento y el nivel geométrico, que incluye módulos para inferir sobre las relaciones espaciales y la viabilidad de las acciones. La tercera parte de la tesis se centra en el uso de la experiencia basada en el conocimiento, llamado conocimiento experiencial, en problemas de manipulación cotidianos, como por ejemplo, en aplicaciones de robótica de servicios, como servir una taza en un entorno desordenado, donde suelen encontrarse algunas habilidades repetibles como recoger, dejar o navegar. Para manejar de manera eficiente estas tareas, en lugar de planificarlas por completo cada vez (lo que podría ser computacionalmente costoso), se propone la integración de módulos para adaptar esas habilidades en diferentes situaciones. En este sentido, se presenta un marco de planificación y ejecución para tareas de manipulación robótica, el cual se equipa de un módulo con conocimiento experiencial (aprendido de su experiencia o dado por el usuario) sobre cómo ejecutar un conjunto de habilidades, tales como recoger, dejar, navegar o abrir un cajón, utilizando flujos de trabajo y trayectorias de robots.