Literatura científica selecionada sobre o tema "Symbolic models"
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Artigos de revistas sobre o assunto "Symbolic models"
Weng, Juyang. "Symbolic Models and Emergent Models: A Review". IEEE Transactions on Autonomous Mental Development 4, n.º 1 (março de 2012): 29–53. http://dx.doi.org/10.1109/tamd.2011.2159113.
Texto completo da fonteTabuada, Paulo. "Symbolic models for control systems". Acta Informatica 43, n.º 7 (16 de janeiro de 2007): 477–500. http://dx.doi.org/10.1007/s00236-006-0036-6.
Texto completo da fonteFang, Meng, Shilong Deng, Yudi Zhang, Zijing Shi, Ling Chen, Mykola Pechenizkiy e Jun Wang. "Large Language Models Are Neurosymbolic Reasoners". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 16 (24 de março de 2024): 17985–93. http://dx.doi.org/10.1609/aaai.v38i16.29754.
Texto completo da fonteWelleck, Sean, Peter West, Jize Cao e Yejin Choi. "Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 8 (28 de junho de 2022): 8629–37. http://dx.doi.org/10.1609/aaai.v36i8.20841.
Texto completo da fonteKelley, Troy D. "Symbolic and Sub-Symbolic Representations in Computational Models of Human Cognition". Theory & Psychology 13, n.º 6 (dezembro de 2003): 847–60. http://dx.doi.org/10.1177/0959354303136005.
Texto completo da fontePasula, H. M., L. S. Zettlemoyer e L. P. Kaelbling. "Learning Symbolic Models of Stochastic Domains". Journal of Artificial Intelligence Research 29 (21 de julho de 2007): 309–52. http://dx.doi.org/10.1613/jair.2113.
Texto completo da fonteLunze, J., e J. Schröder. "Diagnosis Based on Symbolic Dynamical Models". IFAC Proceedings Volumes 33, n.º 11 (junho de 2000): 285–90. http://dx.doi.org/10.1016/s1474-6670(17)37374-3.
Texto completo da fonteBrookes, A., e K. A. Stevens. "Symbolic grouping versus simple cell models". Biological Cybernetics 65, n.º 5 (setembro de 1991): 375–80. http://dx.doi.org/10.1007/bf00216971.
Texto completo da fonteOhlsson, Stellan. "Localist models are already here". Behavioral and Brain Sciences 23, n.º 4 (agosto de 2000): 486–87. http://dx.doi.org/10.1017/s0140525x00443359.
Texto completo da fonteDocquier, N., A. Poncelet e P. Fisette. "ROBOTRAN: a powerful symbolic gnerator of multibody models". Mechanical Sciences 4, n.º 1 (2 de maio de 2013): 199–219. http://dx.doi.org/10.5194/ms-4-199-2013.
Texto completo da fonteTeses / dissertações sobre o assunto "Symbolic models"
Porter, Mark A. "Evolving inferential fermentation models using symbolic annealing". Thesis, University of Newcastle Upon Tyne, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275517.
Texto completo da fonteDevereux, Benet. "Finite-state models with multiplicities, symbolic representation and reasoning". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ62961.pdf.
Texto completo da fonteTownsend, Duncan Clarke McIntire. "Using a symbolic language parser to Improve Markov language models". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100621.
Texto completo da fonteThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 31-32).
This thesis presents a hybrid approach to natural language processing that combines an n-gram (Markov) model with a symbolic parser. In concert these two techniques are applied to the problem of sentence simplification. The n-gram system is comprised of a relational database backend with a frontend application that presents a homogeneous interface for both direct n-gram lookup and Markov approximation. The query language exposed by the frontend also applies lexical information from the START natural language system to allow queries based on part of speech. Using the START natural language system's parser, English sentences are transformed into a collection of structural, syntactic, and lexical statements that are uniquely well-suited to the process of simplification. After reducing the parse of the sentence, the resulting expressions can be processed back into English. These reduced sentences are ranked by likelihood by the n-gram model.
by Duncan Clarke McIntire Townsend.
M. Eng.
Zaner, Frederick Steven. "The development of symbolic models and their extension into space". The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1303495012.
Texto completo da fonteKeyton, Michael M. (Michael Murray). "The Development and Interpretation of Several Symbolic Models of Thought". Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc331860/.
Texto completo da fonteKamienny, Pierre-Alexandre. "Efficient adaptation of reinforcement learning agents : from model-free exploration to symbolic world models". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS412.
Texto completo da fonteReinforcement Learning (RL) encompasses a range of techniques employed to train autonomous agents to interact with environments with the purpose of maximizing their returns across various training tasks. To ensure successful deployment of RL agents in real-world scenarios, achieving generalization and adaptation to unfamiliar situations is crucial. Although neural networks have shown promise in facilitating in-domain generalization by enabling agents to interpolate desired behaviors, their limitations in generalizing beyond the training distribution often lead to suboptimal performance on out-of-distribution data. These challenges are further amplified in RL settings characterized by non-stationary environments and constant distribution shifts during deployment. This thesis presents novel strategies within the framework of Meta-Reinforcement Learning, aiming to equip RL agents with the ability to adapt at test-time to out-of-domain tasks. The first part of the thesis focuses on model-free techniques to learn effective exploration strategies. We consider two scenarios: one where the agent is provided with a set of training tasks, enabling it to explicitly model and learn generalizable task representations; and another where the agent learns without rewards to maximize its state coverage. In the second part, we investigate into the application of symbolic regression, a powerful tool for developing predictive models that offer interpretability and exhibit enhanced robustness against distribution shifts. These models are subsequently integrated within model-based RL agents to improve their performance. Furthermore, this research contributes to the field of symbolic regression by introducing a collection of techniques that leverage Transformer models, enhancing their accuracy and effectiveness. In summary, by addressing the challenges of adaptation and generalization in RL, this thesis focuses on the understanding and application of Meta-Reinforcement Learning strategies. It provides insights and techniques for enabling RL agents to adapt seamlessly to out-of-domain tasks, ultimately facilitating their successful deployment in real-world scenarios
Lampka, Kai. "A symbolic approach to the state graph based analysis of high-level Markov reward models". [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985513926.
Texto completo da fonteRANJAN, MUKESH. "AUTOMATED LAYOUT-INCLUSIVE SYNTHESIS OF ANALOG CIRCUITS USING SYMBOLIC PERFORMANCE MODELS". University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1129922496.
Texto completo da fonteIvanova, Elena. "Efficient Synthesis of Safety Controllers using Symbolic Models and Lazy Algorithms". Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG088.
Texto completo da fonteThis thesis focuses on the development of efficient abstraction-based controller synthesis approaches for cyber-physical systems (CPS). While abstraction-based methods for CPS design have been the subject of intensive research over the last decades, the scalability of these techniques remains an issue. This thesis focus on developing lazy synthesis algorithms for safety specifications. Safety specifications consist in maintaining the trajectory of the system inside a given safe set. This specification is of the utmost importance in many engineering problems, often prioritized over other performance requirements. Lazy approaches outperform the classical synthesis algorithm [Tabuada, 2009] by avoiding computations, which are non-essential for synthesis goals. Chapter 1 motivates the thesis and discusses the state of the art. Chapter 2 structures the existing lazy synthesis approaches and emphasizes three sources of efficiency: information about a priori controllable states, priorities on inputs, and non-reachable from initial set states. Chapter 3 proposes an algorithm, which iteratively explores states on the boundary of controllable domain while avoiding exploration of internal states, supposing that they are safely controllable a priory. A closed-loop safety controller for the original problem is then defined as follows: we use the abstract controller to push the system from a boundary state back towards the interior, while for inner states, any admissible input is valid. Chapter 4 presents an algorithm that restricts the controller synthesis computations to reachable states only while prioritizing longer-duration transitions. The original system is abstracted by a symbolic model with an adaptive grid. Moreover, a novel type of time sampling is also considered. Instead of using transitions of predetermined duration, the duration of the transitions is constrained by state intervals that must contain the reachable set. Chapter 5 is dedicated to monotone transition systems. The introduced lazy synthesis approach benefits from a monotone property of transition systems and the ordered structure of the state (input) space, and the fact that directed safety specifications are considered. The considered class of specifications is then enriched by intersections of upper and lower-closed safety requirements. Chapter 6 concludes the discussion and raises new issues for future research
Salgado, Mauricio. "More than words : computational models of emergence and evolution of symbolic communication". Thesis, University of Surrey, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556464.
Texto completo da fonteLivros sobre o assunto "Symbolic models"
Herdt, Vladimir. Complete Symbolic Simulation of SystemC Models. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-12680-3.
Texto completo da fonteEdwin, Kreuzer, ed. Computerized symbolic manipulation in mechanics. Wien: Springer-Verlag, 1994.
Encontre o texto completo da fonteWolf, Holger C. Anti-tax revolutions and symbolic prosecutions. Cambridge, MA: National Bureau of Economic Research, 1993.
Encontre o texto completo da fonteWolf, Holger. Anti-tax revolutions and symbolic prosecutions. Cambridge, Mass: National Bureau of EconomicResearch, 1993.
Encontre o texto completo da fonteTurner, Raymond. Computable models. London: Springer, 2009.
Encontre o texto completo da fonteKossak, Roman. The structure of models of Peano arithmetic. Oxford: Clarendon, 2006.
Encontre o texto completo da fonteHeckel, J. S. A methodology for linking symbolic and graphical models for collaborative engineering. [Champaign, IL]: US Army Corps of Engineers, Construction Engineering Research Laboratories, 1996.
Encontre o texto completo da fonteHees, Martin van. Rights and decisions: Formal models of law and liberalism. Dordrecht: Kluwer Academic, 1995.
Encontre o texto completo da fonteKrynicki, Michał. Quantifiers: Logics, Models and Computation: Volume Two: Contributions. Dordrecht: Springer Netherlands, 1995.
Encontre o texto completo da fonteClote, Peter. Boolean Functions and Computation Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Symbolic models"
Makridis, Odysseus. "Semantic Models for ∏: ∏⧉". In Symbolic Logic, 351–71. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67396-3_7.
Texto completo da fonteChipere, Ngoni. "Connectionist and Symbolic Models". In Understanding Complex Sentences, 70–87. London: Palgrave Macmillan UK, 2003. http://dx.doi.org/10.1057/9780230005884_4.
Texto completo da fonteHerdt, Vladimir. "Heuristic Symbolic Subsumption". In Complete Symbolic Simulation of SystemC Models, 69–95. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-12680-3_6.
Texto completo da fonteSchreiner, Wolfgang. "Building Models". In Texts & Monographs in Symbolic Computation, 101–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80507-4_4.
Texto completo da fonteFloberg, Henrik. "Transistor Models". In Symbolic Analysis in Analog Integrated Circuit Design, 75–82. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6211-5_7.
Texto completo da fonteDeininger, David, Rayna Dimitrova e Rupak Majumdar. "Symbolic Model Checking for Factored Probabilistic Models". In Automated Technology for Verification and Analysis, 444–60. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46520-3_28.
Texto completo da fonteCastillo, Enrique, José Manuel Gutiérrez e Ali S. Hadi. "Symbolic Propagation of Evidence". In Expert Systems and Probabilistic Network Models, 443–80. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2270-5_10.
Texto completo da fonteSiddiqui, Junaid Haroon, e Sarfraz Khurshid. "Symbolic Execution of Alloy Models". In Formal Methods and Software Engineering, 340–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24559-6_24.
Texto completo da fontePrzigoda, Nils, Robert Wille, Judith Przigoda e Rolf Drechsler. "A Symbolic Formulation for Models". In Automated Validation & Verification of UML/OCL Models Using Satisfiability Solvers, 25–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72814-8_3.
Texto completo da fonteAberer, Karl. "Combinatory models and symbolic computation". In Design and Implementation of Symbolic Computation Systems, 116–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57272-4_29.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Symbolic models"
Khalil, Amal, e Juergen Dingel. "Incremental symbolic execution of evolving state machines". In 2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2015. http://dx.doi.org/10.1109/models.2015.7338231.
Texto completo da fonteGreenyer, Joel, e Timo Gutjahr. "Symbolic Execution for Realizability-Checking of Scenario-Based Specifications". In 2017 ACM/IEEE 20th International Conference on Model-Driven Engineering Languages and Systems (MODELS). IEEE, 2017. http://dx.doi.org/10.1109/models.2017.35.
Texto completo da fonteChang, Felix Sheng-Ho, e Daniel Jackson. "Symbolic model checking of declarative relational models". In Proceeding of the 28th international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1134285.1134329.
Texto completo da fonteDeVries, Byron, e Betty H. C. Cheng. "Automatic detection of incomplete requirements via symbolic analysis". In MODELS '16: ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2976767.2976791.
Texto completo da fonteCederbladh, Johan, Loek Cleophas, Eduard Kamburjan, Lucas Lima e Hans Vangheluwe. "Symbolic Reasoning for Early Decision-Making in Model-Based Systems Engineering". In 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2023. http://dx.doi.org/10.1109/models-c59198.2023.00117.
Texto completo da fonteJames, Steven. "Learning Portable Symbolic Representations". In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/826.
Texto completo da fonteBaras, Karolina, A. Moreira e F. Meneses. "Navigation based on symbolic space models". In 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2010. http://dx.doi.org/10.1109/ipin.2010.5646810.
Texto completo da fonteJacomme, Charlie, Steve Kremer e Guillaume Scerri. "Symbolic Models for Isolated Execution Environments". In 2017 IEEE European Symposium on Security and Privacy (EuroS&P). IEEE, 2017. http://dx.doi.org/10.1109/eurosp.2017.16.
Texto completo da fonteJeon, Jinseong, Xiaokang Qiu, Jonathan Fetter-Degges, Jeffrey S. Foster e Armando Solar-Lezama. "Synthesizing framework models for symbolic execution". In ICSE '16: 38th International Conference on Software Engineering. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2884781.2884856.
Texto completo da fonteZhao, Siang, Zhongyang Li, Zhenbang Chen e Ji Wang. "Symbolic Verification of Fuzzy Logic Models". In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2023. http://dx.doi.org/10.1109/ase56229.2023.00087.
Texto completo da fonteRelatórios de organizações sobre o assunto "Symbolic models"
VanLehn, Kurt. Analysis of Symbolic Parameter Models. Fort Belvoir, VA: Defense Technical Information Center, março de 1993. http://dx.doi.org/10.21236/ada261930.
Texto completo da fonteYang, Bwolen, Reid Simmons, Randal E. Bryant e David R. O'Hallaron. Optimizing Symbolic Model Checking for Constraint-Rich Models. Fort Belvoir, VA: Defense Technical Information Center, março de 1999. http://dx.doi.org/10.21236/ada363778.
Texto completo da fonteCampos, Sergio V., e Edmund M. Clarke. Real-Time Symbolic Model Checking for Discrete Time Models. Fort Belvoir, VA: Defense Technical Information Center, maio de 1994. http://dx.doi.org/10.21236/ada282878.
Texto completo da fonteGardner, Daniel. Symbolic Processor Based Models of Neural Networks. Fort Belvoir, VA: Defense Technical Information Center, maio de 1988. http://dx.doi.org/10.21236/ada200200.
Texto completo da fontePolk, Thad A., Kurt VanLehn e Dirk Kalp. ASPM2: Progress Toward the Analysis of Symbolic Parameter Models. Fort Belvoir, VA: Defense Technical Information Center, setembro de 1994. http://dx.doi.org/10.21236/ada284437.
Texto completo da fonteVanLehn, Kurt. Analysis of Symbolic Models of Cognition Project (ASPM-Pitt). Fort Belvoir, VA: Defense Technical Information Center, setembro de 1992. http://dx.doi.org/10.21236/ada255929.
Texto completo da fonteSayer, Catherine, e Martin Doherty. The classic model room task: A symbol that doesn’t measure symbolism. Peeref, junho de 2023. http://dx.doi.org/10.54985/peeref.2306p4947936.
Texto completo da fonteBiere, Armin, Alessandro Cimatti, Edmund Clark e Yunshan Zhu. Symbolic Model Checking without BDDs. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1999. http://dx.doi.org/10.21236/ada360973.
Texto completo da fonteGovindaraju, Shankar G., e David L. Dill. Approximate Symbolic Model Checking Using Overlapping Projections. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1999. http://dx.doi.org/10.21236/ada401014.
Texto completo da fonteBaader, Franz, e Klaus U. Schulz. Unification Theory - An Introduction. Aachen University of Technology, 1997. http://dx.doi.org/10.25368/2022.135.
Texto completo da fonte