Zeitschriftenartikel: „Symbolic models“

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Weng, Juyang. „Symbolic Models and Emergent Models: A Review“. IEEE Transactions on Autonomous Mental Development 4, Nr. 1 (März 2012): 29–53. http://dx.doi.org/10.1109/tamd.2011.2159113.

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Tabuada, Paulo. „Symbolic models for control systems“. Acta Informatica 43, Nr. 7 (16.01.2007): 477–500. http://dx.doi.org/10.1007/s00236-006-0036-6.

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3

Fang, Meng, Shilong Deng, Yudi Zhang, Zijing Shi, Ling Chen, Mykola Pechenizkiy und Jun Wang. „Large Language Models Are Neurosymbolic Reasoners“. Proceedings of the AAAI Conference on Artificial Intelligence 38, Nr. 16 (24.03.2024): 17985–93. http://dx.doi.org/10.1609/aaai.v38i16.29754.

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A wide range of real-world applications is characterized by their symbolic nature, necessitating a strong capability for symbolic reasoning. This paper investigates the potential application of Large Language Models (LLMs) as symbolic reasoners. We focus on text-based games, significant benchmarks for agents with natural language capabilities, particularly in symbolic tasks like math, map reading, sorting, and applying common sense in text-based worlds. To facilitate these agents, we propose an LLM agent designed to tackle symbolic challenges and achieve in-game objectives. We begin by initializing the LLM agent and informing it of its role. The agent then receives observations and a set of valid actions from the text-based games, along with a specific symbolic module. With these inputs, the LLM agent chooses an action and interacts with the game environments. Our experimental results demonstrate that our method significantly enhances the capability of LLMs as automated agents for symbolic reasoning, and our LLM agent is effective in text-based games involving symbolic tasks, achieving an average performance of 88% across all tasks.

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Welleck, Sean, Peter West, Jize Cao und Yejin Choi. „Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics“. Proceedings of the AAAI Conference on Artificial Intelligence 36, Nr. 8 (28.06.2022): 8629–37. http://dx.doi.org/10.1609/aaai.v36i8.20841.

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Neural sequence models trained with maximum likelihood estimation have led to breakthroughs in many tasks, where success is defined by the gap between training and test performance. However, their ability to achieve stronger forms of generalization remains unclear. We consider the problem of symbolic mathematical integration, as it requires generalizing systematically beyond the training set. We develop a methodology for evaluating generalization that takes advantage of the problem domain's structure and access to a verifier. Despite promising in-distribution performance of sequence-to-sequence models in this domain, we demonstrate challenges in achieving robustness, compositionality, and out-of-distribution generalization, through both carefully constructed manual test suites and a genetic algorithm that automatically finds large collections of failures in a controllable manner. Our investigation highlights the difficulty of generalizing well with the predominant modeling and learning approach, and the importance of evaluating beyond the test set, across different aspects of generalization.

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Kelley, Troy D. „Symbolic and Sub-Symbolic Representations in Computational Models of Human Cognition“. Theory & Psychology 13, Nr. 6 (Dezember 2003): 847–60. http://dx.doi.org/10.1177/0959354303136005.

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Pasula, H. M., L. S. Zettlemoyer und L. P. Kaelbling. „Learning Symbolic Models of Stochastic Domains“. Journal of Artificial Intelligence Research 29 (21.07.2007): 309–52. http://dx.doi.org/10.1613/jair.2113.

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In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a probabilistic, relational planning rule representation that compactly models noisy, nondeterministic action effects, and show how such rules can be effectively learned. Through experiments in simple planning domains and a 3D simulated blocks world with realistic physics, we demonstrate that this learning algorithm allows agents to effectively model world dynamics.

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Lunze, J., und J. Schröder. „Diagnosis Based on Symbolic Dynamical Models“. IFAC Proceedings Volumes 33, Nr. 11 (Juni 2000): 285–90. http://dx.doi.org/10.1016/s1474-6670(17)37374-3.

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Brookes, A., und K. A. Stevens. „Symbolic grouping versus simple cell models“. Biological Cybernetics 65, Nr. 5 (September 1991): 375–80. http://dx.doi.org/10.1007/bf00216971.

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Ohlsson, Stellan. „Localist models are already here“. Behavioral and Brain Sciences 23, Nr. 4 (August 2000): 486–87. http://dx.doi.org/10.1017/s0140525x00443359.

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Localist networks are symbolic models, because their nodes refer to extra-mental objects and events. Hence, localist networks can be combined with symbolic computations to form hybrid models. Such models are already familiar and they are likely to represent the dominant type of cognitive model in the next few decades.

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Docquier, N., A. Poncelet und P. Fisette. „ROBOTRAN: a powerful symbolic gnerator of multibody models“. Mechanical Sciences 4, Nr. 1 (02.05.2013): 199–219. http://dx.doi.org/10.5194/ms-4-199-2013.

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Abstract. The computational efficiency of symbolic generation was at the root of the emergence of symbolic multibody programs in the eighties. At present, it remains an attractive feature of it since the exponential increase in modern computer performances naturally provides the opportunity to investigate larger systems and more sophisticated models for which real-time computation is a real asset. Nowadays, in the context of mechatronic multibody systems, another interesting feature of the symbolic approach appears when dealing with enlarged multibody models, i.e. including electrical actuators, hydraulic devices, pneumatic suspensions, etc. and requiring specific analyses like control and optimization. Indeed, since symbolic multibody programs clearly distinguish the modeling phase from the analysis process, extracting the symbolic model, as well as some precious ingredients like analytical sensitivities, in order to export it towards any suitable environment (for control or optimization purposes) is quite straightforward. Symbolic multibody model portability is thus very attractive for the analysis of mechatronic applications. In this context, the main features and recent developments of the ROBOTRAN software developed at the Université catholique de Louvain (Belgium) are reviewed in this paper and illustrated via three multibody applications which highlight its capabilities for dealing with very large systems and coping with multiphysics issues.

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Chacón, Jose Emmanuel, und Oldemar Rodríguez. „Regression Models for Symbolic Interval-Valued Variables“. Entropy 23, Nr. 4 (06.04.2021): 429. http://dx.doi.org/10.3390/e23040429.

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This paper presents new approaches to fit regression models for symbolic internal-valued variables, which are shown to improve and extend the center method suggested by Billard and Diday and the center and range method proposed by Lima-Neto, E.A.and De Carvalho, F.A.T. Like the previously mentioned methods, the proposed regression models consider the midpoints and half of the length of the intervals as additional variables. We considered various methods to fit the regression models, including tree-based models, K-nearest neighbors, support vector machines, and neural networks. The approaches proposed in this paper were applied to a real dataset and to synthetic datasets generated with linear and nonlinear relations. For an evaluation of the methods, the root-mean-squared error and the correlation coefficient were used. The methods presented herein are available in the the RSDA package written in the R language, which can be installed from CRAN.

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Phong, Phạm Hồng, und Bùi Công Cường. „Symbolic Computational Models for Intuitionistic Linguistic Information“. Journal of Computer Science and Cybernetics 32, Nr. 1 (07.06.2016): 31–45. http://dx.doi.org/10.15625/1813-9663/32/1/5984.

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In \cite{Cuong14, Phong14}, we first introduced the notion of intuitionistic linguistic labels. In this paper, we develop two symbolic computational models for intuitionistic linguistic labels (intuitionistic linguistic information). Various operators are proposed, their properties are also examined. Then, an application in group decision making using intuitionistic linguistic preference relations is discussed.

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Fisette, P., T. Postiau, L. Sass und J. C. Samin. „FULLY SYMBOLIC GENERATION OF COMPLEX MULTIBODY MODELS*“. Mechanics of Structures and Machines 30, Nr. 1 (31.01.2002): 31–82. http://dx.doi.org/10.1081/sme-120001477.

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Zhanatauov, S. U. „VERBAL, SYMBOLIC, MATHEMATICAL, SEMANTIC, BEHAVIORAL, COGNITIVE MODELS.“ Theoretical & Applied Science 113, Nr. 09 (30.09.2022): 169–74. http://dx.doi.org/10.15863/tas.2022.09.113.32.

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Kwatny, H. G., und G. L. Blankenship. „Symbolic construction of models for multibody dynamics“. IEEE Transactions on Robotics and Automation 11, Nr. 2 (April 1995): 271–81. http://dx.doi.org/10.1109/70.370509.

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Pola, Giordano, Pierdomenico Pepe und Maria Domenica Di Benedetto. „Symbolic Models for Networks of Control Systems“. IEEE Transactions on Automatic Control 61, Nr. 11 (November 2016): 3663–68. http://dx.doi.org/10.1109/tac.2016.2528046.

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Jagtap, Pushpak, und Majid Zamani. „Symbolic models for retarded jump–diffusion systems“. Automatica 111 (Januar 2020): 108666. http://dx.doi.org/10.1016/j.automatica.2019.108666.

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Zeng, Yifeng, und Kim-leng Poh. „Symbolic verification of multiagent graphical decision models“. International Journal of Intelligent Systems 23, Nr. 11 (November 2008): 1177–95. http://dx.doi.org/10.1002/int.20313.

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Navarro, Vicente, Arianna Pucci, Erik Tengblad, Francesca Casini und Laura Asensio. „Symbolic algebra integration of soil elastoplastic models“. Computers and Geotechnics 164 (Dezember 2023): 105834. http://dx.doi.org/10.1016/j.compgeo.2023.105834.

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do Nascimento, Rafaella L. S., Renata M. C. R. de Souza und Francisco José de A. Cysneiros. „Generalized linear models for symbolic polygonal data“. Knowledge-Based Systems 290 (April 2024): 111569. http://dx.doi.org/10.1016/j.knosys.2024.111569.

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Han, Sung Ho, Bang Nguyen und Lyndon Simkin. „The dynamic models of consumers’ symbolic needs: in the context of restaurant brands“. European Journal of Marketing 50, Nr. 7/8 (11.07.2016): 1348–76. http://dx.doi.org/10.1108/ejm-03-2015-0144.

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Purpose The purpose of this paper is to investigate the dynamic process and the meaning of symbolic consumption according to the three symbolic needs (i.e. status needs, social needs, status and social needs) to understand how symbolic messages are conveyed when consumers choose a brand. Design/methodology/approach This paper develops three dynamic models, categorized according to the consumers’ needs. The conceptual framework consists of the six constructs: collectivism/individualism, brand reputation, self-congruence, brand affect, brand identification and brand loyalty. Twelve hypotheses were developed and tested. Data were collected from consumers who had experienced well-known global chain restaurant brands. The three models were tested using confirmatory factor analysis and structural equation modelling. Findings Findings highlight the important mediating role of brand affect in symbolic consumption, which previously has not been revealed empirically. Moreover, it is found that self-congruence does not mediate the relationship between brand reputation, collectivism/individualism and brand affect, despite its prominence in previous symbolic consumption studies. In the status and social needs models, brand reputation mediates between collectivism/individualism and self-congruence, brand identification, brand affect and brand loyalty. Originality/value This is the first empirical paper to investigate symbolic consumption in the context of three types of models, according to symbolic needs, in the context of restaurant consumption. The study also identifies the major components of the consumer’s symbolic needs based on the attributes of symbolic consumption. Moreover, this study reveals that when both social needs and status needs are mixed, a hierarchy exists between consumers’ symbolic needs. Finally, the study makes an important contribution to the literature by applying the concept of brand affect to symbolic consumption research and exploring the relationships between the external motivational factors and the internal elements of symbolic consumption.

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LUCAS, PETER. „Symbolic diagnosis and its formalisation“. Knowledge Engineering Review 12, Nr. 2 (Juni 1997): 109–46. http://dx.doi.org/10.1017/s0269888997002026.

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Diagnosis was among the first subjects investigated when digital computers became available. It still remains an important research area, in which several new developments have taken place in the last decade. One of these new developments is the use of detailed domain models in knowledge-based systems for the purpose of diagnosis, often referred to as “model-based” diagnosis. Typically, such models embody knowledge of the normal or abnormal structure and behaviour of the modelled objects in a domain. Models of the structure and workings of technical devices, and causal models of disease processes in medicine are two examples. In this article, the most important notions of diagnosis and their formalisation are reviewed and brought in perspec tive. In addition, attention is focused on a number of general frameworks of diagnosis, which offer sufficient flexibility for expressing several types of diagnosis.

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Stepanovic, Ivana, Dragica Pavlovic-Babic und Zora Krnjaic. „The analysis of actual and symbolic models of secondary school students in Serbia“. Zbornik Instituta za pedagoska istrazivanja 41, Nr. 2 (2009): 401–17. http://dx.doi.org/10.2298/zipi0902401s.

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This paper deals with role models of secondary school students in Serbia. In the course of adolescence, there is a gradual separation from parental figures, and other persons become role models for behavior. For that reason, secondary school population is of interest when analyzing this phenomenon, particularly bearing in mind that role models influence not only social, but also other aspects of development. We analyzed role models from students' personal (actual models) and public life (symbolic models). The main aim was to determine who their actual and symbolic models are, and why secondary school students look up to them. Based on the data on secondary school students' actual models, it is possible to identify who important persons from their milieu are and why they are important to them. The data about the categories in which symbolic models can be divided, as well as about their occurrence, indicate the young people's system of values in these analyses. The sample comprises 2426 students from 26 schools in 9 Serbian towns. Actual and symbolic models were examined in separate questions, where students were asked to name up to three people from their private life or the world of celebrities that they look up to. 53,9% of students named their actual models, the most common being their mothers. Nearly half the examinees (49,3%) stated their symbolic models are public figures. Most symbolic models are from the world of show-business. The results show that parental figures remain the models of behavior throughout adolescence. The data about the categories of symbolic models show the young are drawn to the world of entertainment and indicate a weak role of schools as a potential source of models in the fields of science and culture who would promote cognitive values.

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Swikir, Abdalla, Navid Noroozi und Majid Zamani. „Compositional Synthesis of Symbolic Models for Infinite Networks“. IFAC-PapersOnLine 53, Nr. 2 (2020): 1868–73. http://dx.doi.org/10.1016/j.ifacol.2020.12.2356.

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Neto, Eufrásio de A. Lima, Gauss M. Cordeiro und Francisco de A. T. de Carvalho. „Bivariate symbolic regression models for interval-valued variables“. Journal of Statistical Computation and Simulation 81, Nr. 11 (November 2011): 1727–44. http://dx.doi.org/10.1080/00949655.2010.500470.

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Swikir, Abdalla, Antoine Girard und Majid Zamani. „Symbolic Models for a Class of Impulsive Systems“. IEEE Control Systems Letters 5, Nr. 1 (Januar 2021): 247–52. http://dx.doi.org/10.1109/lcsys.2020.3001501.

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Jackson, Janet L., Aladin Akyürek und John A. Michon. „Symbolic and other Cognitive Models of Temporal Reality“. Time & Society 2, Nr. 2 (Mai 1993): 241–56. http://dx.doi.org/10.1177/0961463x93002002006.

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Kirćanski, N., T. Davidović und M. Vukobratović. „A contribution to parallelization of symbolic robot models“. Robotica 13, Nr. 4 (Juli 1995): 411–21. http://dx.doi.org/10.1017/s0263574700018841.

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SummaryThis paper is focused on task scheduling in multiprocessor robot controllers. To minimize the input-output time delay our consideration is restricted to parallel architectures that include complete crossbar interconnection networks. In this paper, an efficient scheduling algorithm based on a heuristic function is considered. This function takes into account delays caused by interprocessor communication and minimizes both the execution time and the communication cost. Robot control computation based on a highly efficient customized symbolic method is decomposed into a large number of simple tasks, each involving a single floating-point operation. Starting with an empty partial schedule, each step of the search extends the current partial schedule by adding one of the tasks yet to be scheduled. The heuristic function used in the algorithm actively directs the search for a feasible schedule, i.e. it helps choose the task that extends the current partial schedule. To increase the computational rate we introduced overlapping of computations.

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D�hmen, Gert, Ronald Herrmann und Hergen Pargmann. „Translating VHDL into functional symbolic finite-state models“. Formal Methods in System Design 7, Nr. 1-2 (August 1995): 125–48. http://dx.doi.org/10.1007/bf01383876.

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Pola, Giordano, Antoine Girard und Paulo Tabuada. „Approximately bisimilar symbolic models for nonlinear control systems“. Automatica 44, Nr. 10 (Oktober 2008): 2508–16. http://dx.doi.org/10.1016/j.automatica.2008.02.021.

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Charrier, Tristan, Sophie Pinchinat und FranÇois Schwarzentruber. „Symbolic model checking of public announcement protocols“. Journal of Logic and Computation 29, Nr. 8 (Dezember 2019): 1211–49. http://dx.doi.org/10.1093/logcom/exz023.

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Abstract We study the symbolic model checking problem against public announcement protocol logic (PAPL), featuring protocols with public announcements, arbitrary public announcements and group announcements. Technically, symbolic models are Kripke models whose accessibility relations are presented as programs described in a dynamic logic style with propositional assignments. We highlight the relevance of such symbolic models and show that the symbolic model checking problem against PAPL is A$_{\textrm{pol}}$Exptime-complete as soon as announcement protocols allow for either arbitrary announcements or iteration of public announcements. However, when both options are discarded, the complexity drops to Pspace-complete.

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Marra, Giuseppe. „Bridging symbolic and subsymbolic reasoning with minimax entropy models“. Intelligenza Artificiale 15, Nr. 2 (04.02.2022): 71–90. http://dx.doi.org/10.3233/ia-210088.

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In this paper, we investigate MiniMax Entropy models, a class of neural symbolic models where symbolic and subsymbolic features are seamlessly integrated. We show how these models recover classical algorithms from both the deep learning and statistical relational learning scenarios. Novel hybrid settings are defined and experimentally explored, showing state-of-the-art performance in collective classification, knowledge base completion and graph (molecular) data generation.

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Desain, Peter. „A connectionist and a traditional AI quantizer, symbolic versus sub-symbolic models of rhythm perception“. Contemporary Music Review 9, Nr. 1-2 (Januar 1993): 239–54. http://dx.doi.org/10.1080/07494469300640471.

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Feistel, Rainer. „Self-Organisation of Prediction Models“. Entropy 25, Nr. 12 (28.11.2023): 1596. http://dx.doi.org/10.3390/e25121596.

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Living organisms are active open systems far from thermodynamic equilibrium. The ability to behave actively corresponds to dynamical metastability: minor but supercritical internal or external effects may trigger major substantial actions such as gross mechanical motion, dissipating internally accumulated energy reserves. Gaining a selective advantage from the beneficial use of activity requires a consistent combination of sensual perception, memorised experience, statistical or causal prediction models, and the resulting favourable decisions on actions. This information processing chain originated from mere physical interaction processes prior to life, here denoted as structural information exchange. From there, the self-organised transition to symbolic information processing marks the beginning of life, evolving through the novel purposivity of trial-and-error feedback and the accumulation of symbolic information. The emergence of symbols and prediction models can be described as a ritualisation transition, a symmetry-breaking kinetic phase transition of the second kind previously known from behavioural biology. The related new symmetry is the neutrally stable arbitrariness, conventionality, or code invariance of symbols with respect to their meaning. The meaning of such symbols is given by the structural effect they ultimately unleash, directly or indirectly, by deciding on which actions to take. The early genetic code represents the first symbols. The genetically inherited symbolic information is the first prediction model for activities sufficient for survival under the condition of environmental continuity, sometimes understood as the “final causality” property of the model.

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Nørreklit, Hanne. „Managing individuality: myths versus art“. Proceedings of Pragmatic Constructivism 1, Nr. 2 (01.09.2011): 35–44. http://dx.doi.org/10.7146/propracon.v1i2.16664.

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The purpose of this article is to establish the symbolic forms that are presently used in selected mainstream management models and to assess whether the connection between leadership and individual human reality would be improved if the management models were fundamentally inspired by those used by a successful manager and artist.The theoretical starting point of this article is Cassirer’s (Cassirer 1999) philosophy of symbolic forms. A symbolic form is “a way of having a life world” (own translation) (Cassirer 1999). In a symbolic form, a person discovers and unfolds an ability to build his own universe as an ideal universe which enables the person to “understand and interpret, to articulate and organize, synthesize and universalize his human experience” (Cassirer 1962: 221). Symbolic forms such as art, science, myth and religion thus have common features and structures in their basic function of creating common human existence. When the symbolic form is science, ideals of objectivity and precision in the description of phenomena and their relations dominate man’s formation of his universe. In art, man unfolds an ability to be subjective and create empathetic insight into matters and their diversity (Cassirer 1962). Where science as symbolic form conceptualizes objects, art teaches us empathetic insight. The symbolic forms of art and science perceive a phenomenon differently. For example, science will perhaps see a constellation as a trigonometric function, whereas it may be considered by art as a “Hogarthian shape of beauty” (own translation) (Cassirer 1999: 62). Like the symbolic form of art, the symbolic form of myth builds on emotional sympathy, but differs by believing in the existence of the constellation. It is used to create a natural or magical unity of life. Monotheistic religions also include ideas of striving for a sense of unity, but here the idea is to achieve a universal, ethical sense of unity in an individualized society. Thus the symbolic form of religion helps the individual to choose between right and wrong.With this in mind, we examine the use of symbolic forms embedded in selected mainstream management models. Subsequently, we study the symbolic forms embedded in the management discourse as the concept is unfolded by the successful Artistic Director of the Royal Danish Opera, Kasper Holten, when he talks about management, with a view to determining the extent to which this practice differs from the symbolic forms embedded in the mainstream management models. The analysis shows that mainstream management models are primarily rooted in the symbolic form of science, although they tend to gradually include the symbolic form of religion or the symbolic form of myth. Generally speaking, the mainstream management models tend to exercise power over the individual’s emphatic insight and autonomous reflection and thereby constrain the scope for human creativity and individuality. Distinctively, Kasper Holten’s management discourse integrates the symbolic forms of art and science. With art as the dominant symbolic form, Kasper rejects new public management’s perception about opera and the management of art while at the same time – through discourses that bind to the individuality of the network of players – forming personal and social identities which come together to realize a world of existential ideas about operas in general as well as opera in particular.The article is relevant because it provides insight into the ways in which management models, through the use of myth and science as symbolic forms, exercise influence on human existence and interaction and thereby influence the scope for human freedom and exercise of power and also because it provides insight into the features and structures concerning human existence and co-existence from which mainstream management models cut themselves off by not using art as a form of consciousness. The constructive aspect is a parallel outline of features and structures in a new management discourse which are better suited for postmodern society.

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Cline, Terry, Harold Abelson und Warren Harris. „Symbolic computing in engineering design“. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 3, Nr. 3 (August 1989): 195–206. http://dx.doi.org/10.1017/s0890060400001220.

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Computer programs that combine traditional numeric methods with symbolic algebra and with specific knowledge of application-based techniques can provide new levels of computational support for engineering design. We illustrate this with a computer-based ‘control engineer’s assistant’. Although this program is focussed on control system design, it demonstrates techniques that should be widely applicable across many engineering disciplines. In particular, we show how, with symbolic computing, a computer-aided design system can usefully simulate engineering models early in the design process, before all (or any) system parameters have been specified numerically. Our system employs a flexible, extensible, object-oriented representation for control systems, which admits multiple mathematical models of designs and provides a framework for integrating tools that operate on diverse representations.

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Dickens, Charles, Connor Pryor und Lise Getoor. „Modeling Patterns for Neural-Symbolic Reasoning Using Energy-based Models“. Proceedings of the AAAI Symposium Series 3, Nr. 1 (20.05.2024): 90–99. http://dx.doi.org/10.1609/aaaiss.v3i1.31187.

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Neural-symbolic (NeSy) AI strives to empower machine learning and large language models with fast, reliable predictions that exhibit commonsense and trustworthy reasoning by seamlessly integrating neural and symbolic methods. With such a broad scope, several taxonomies have been proposed to categorize this integration, emphasizing knowledge representation, reasoning algorithms, and applications. We introduce a knowledge representation-agnostic taxonomy focusing on the neural-symbolic interface capturing methods that reason with probability, logic, and arithmetic constraints. Moreover, we derive expressions for gradients of a prominent class of learning losses and a formalization of reasoning and learning. Through a rigorous empirical analysis spanning three tasks, we show NeSy approaches reach up to a 37% improvement over neural baselines in a semi-supervised setting and a 19% improvement over GPT-4 on question-answering.

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Liu, Chuang. „Symbolic versus Modelistic Elements in Scientific Modeling“. THEORIA. An International Journal for Theory, History and Foundations of Science 30, Nr. 2 (20.06.2015): 287. http://dx.doi.org/10.1387/theoria.12863.

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In this paper, we argue that symbols (or the symbolic) are conventional vehicles whose chief function is denotation, while models (or the modelistic) are epistemic vehicles, and their chief function is to show what their targets are like in the relevant aspects. Although the same object may serve both functions, the two vehicles are <em>conceptually distinct</em> and <em>most</em> models employ both elements. Together with this point we offer an alternative to the deflationary view on scientific models. In addition, we point out there are non-referring models in which symbols label model components. We show how Goodman’s view on pictures of fictional characters provides a way to understand such models and how it further reveal the distinction between the symbolic and the modelistic representation.

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Giannarakis, Nick, Alexandra Silva und David Walker. „ProbNV: probabilistic verification of network control planes“. Proceedings of the ACM on Programming Languages 5, ICFP (22.08.2021): 1–30. http://dx.doi.org/10.1145/3473595.

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ProbNV is a new framework for probabilistic network control plane verification that strikes a balance between generality and scalability. ProbNV is general enough to encode a wide range of features from the most common protocols (eBGP and OSPF) and yet scalable enough to handle challenging properties, such as probabilistic all-failures analysis of medium-sized networks with 100-200 devices. When there are a small, bounded number of failures, networks with up to 500 devices may be verified in seconds. ProbNV operates by translating raw CISCO configurations into a probabilistic and functional programming language designed for network verification. This language comes equipped with a novel type system that characterizes the sort of representation to be used for each data structure: concrete for the usual representation of values; symbolic for a BDD-based representation of sets of values; and multi-value for an MTBDD-based representation of values that depend upon symbolics. Careful use of these varying representations speeds execution of symbolic simulation of network models. The MTBDD-based representations are also used to calculate probabilistic properties of network models once symbolic simulation is complete. We implement the language and evaluate its performance on benchmarks constructed from real network topologies and synthesized routing policies.

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Coelho, A. A., J. Evans, I. Evans, A. Kern und S. Parsons. „The TOPAS symbolic computation system“. Powder Diffraction 26, S1 (Dezember 2011): S22—S25. http://dx.doi.org/10.1154/1.3661087.

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Computer algebra removes much of the drudgery from mathematics; it allows users to formulate models by using the language of mathematics and to have those models evaluated with little effort. This symbolic form of representation is often thought of as being separate to dedicated computational programs such as Rietveld refinement. These dedicated programs are often written in low level languages; they are relatively inflexible in what they do and modifying them to change functionality in a small manner is often a major programming task. This paper describes a symbolic system that is integrated into the dedicated Rietveld refinement program called TOPAS. The symbolic component allows large functional changes to be made at run time and with a relatively small amount of effort. In addition, the system as a whole reduces the programming complexity at the developmental stage.

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Sanner, Scott, und Ehsan Abbasnejad. „Symbolic Variable Elimination for Discrete and Continuous Graphical Models“. Proceedings of the AAAI Conference on Artificial Intelligence 26, Nr. 1 (20.09.2021): 1954–60. http://dx.doi.org/10.1609/aaai.v26i1.8406.

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Probabilistic reasoning in the real-world often requires inference incontinuous variable graphical models, yet there are few methods for exact, closed-form inference when joint distributions are non-Gaussian. To address this inferential deficit, we introduce SVE -- a symbolic extension of the well-known variable elimination algorithm to perform exact inference in an expressive class of mixed discrete and continuous variable graphical models whose conditional probability functions can be well-approximated as piecewise combinations of polynomials with bounded support. Using this representation, we show that we can compute all of the SVE operations exactly and in closed-form, which crucially includes definite integration w.r.t. multivariate piecewise polynomial functions. To aid in the efficient computation and compact representation of this solution, we use an extended algebraic decision diagram (XADD) data structure that supports all SVE operations. We provide illustrative results for SVE on probabilistic inference queries inspired by robotics localization and tracking applications that mix various continuous distributions; this represents the first time a general closed-form exact solution has been proposed for this expressive class of discrete/continuous graphical models.

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Ben Hassan Saïdi, Ismaïl, Martin Schmelzer, Paola Cinnella und Francesco Grasso. „CFD-driven symbolic identification of algebraic Reynolds-stress models“. Journal of Computational Physics 457 (Mai 2022): 111037. http://dx.doi.org/10.1016/j.jcp.2022.111037.

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Girard, A., G. Pola und P. Tabuada. „Approximately Bisimilar Symbolic Models for Incrementally Stable Switched Systems“. IEEE Transactions on Automatic Control 55, Nr. 1 (Januar 2010): 116–26. http://dx.doi.org/10.1109/tac.2009.2034922.

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Zamani, Majid, Giordano Pola, Manuel Mazo und Paulo Tabuada. „Symbolic Models for Nonlinear Control Systems Without Stability Assumptions“. IEEE Transactions on Automatic Control 57, Nr. 7 (Juli 2012): 1804–9. http://dx.doi.org/10.1109/tac.2011.2176409.

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Meyer, Pierre-Jean, Antoine Girard und Emmanuel Witrant. „Compositional Abstraction and Safety Synthesis Using Overlapping Symbolic Models“. IEEE Transactions on Automatic Control 63, Nr. 6 (Juni 2018): 1835–41. http://dx.doi.org/10.1109/tac.2017.2753039.

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Bozzano, Marco, Alessandro Cimatti, Oleg Lisagor, Cristian Mattarei, Sergio Mover, Marco Roveri und Stefano Tonetta. „Safety assessment of AltaRica models via symbolic model checking“. Science of Computer Programming 98 (Februar 2015): 464–83. http://dx.doi.org/10.1016/j.scico.2014.06.003.

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Krupski, Vladimir N. „On symbolic models for Single-Conclusion Logic of Proofs“. Sbornik: Mathematics 202, Nr. 5 (31.05.2011): 683–95. http://dx.doi.org/10.1070/sm2011v202n05abeh004161.

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Balarin, Felice. „Concurrent Symbolic Verification of Liveness Properties for Interleaved Models“. Electronic Notes in Theoretical Computer Science 23, Nr. 2 (Dezember 2001): 1–10. http://dx.doi.org/10.1016/s1571-0661(04)80664-9.

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Prudêncio, Ricardo B. C., Teresa B. Ludermir und Francisco de A. T. de Carvalho. „A Modal Symbolic Classifier for selecting time series models“. Pattern Recognition Letters 25, Nr. 8 (Juni 2004): 911–21. http://dx.doi.org/10.1016/j.patrec.2004.02.004.

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Pola, Giordano, und Paulo Tabuada. „Symbolic Models for Nonlinear Control Systems: Alternating Approximate Bisimulations“. SIAM Journal on Control and Optimization 48, Nr. 2 (Januar 2009): 719–33. http://dx.doi.org/10.1137/070698580.

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