Towards a model-theoretic framework for describing the semantic aspects of cognitive processes
Abstract Semantics is one of the most challenging aspects of cognitive architectures. Mathematical logic, or linguistics, highlights that semantics is essential to human cognition. The Cognitive Theory of True Conditions (CTTC) is a proposal to implement cognitive abilities and to describe the semantics of symbolic cognitive architectures based on model-theoretic semantics. This article focuses on the concepts supporting the mathematical formulation of the CTTC, its relationship to other proposals, and how it can be used as a framework for designing cognitive abilities in agents.
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Barsalou, L., 2008. Grounded Cognition. Annual Review of Psychology, 59(1):617-645. - https://doi.org/10.1146/annurev.psych.59.103006.093639
Barsalou, L., 2010. Grounded Cognition: Past, Present, and Future. Topics in Cognitive Science, 2(4):716-724. Brachman, R. and Levesque, H., 2004. Knowledge Representation and Reasoning. Morgan Kaufmann. - https://doi.org/10.1111/j.1756-8765.2010.01115.x
Davidson, D., 1967. Truth and Meaning. Synthese, 17(3):304-323. Davidson, D., 2005. Truth and Predication. Harvard University Press. - https://doi.org/10.1007/BF00485035
Gödel, K., 1931. Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I. - https://doi.org/10.1007/BF01700692
Monatshefte für Mathematik und Physik, 38(1):173-198.
Jacques, P. et al., 2018. Remembering and imagining alternative versions of the personal past. Neuropsychologia, 110:170-179. - https://doi.org/10.1016/j.neuropsychologia.2017.06.015
Johnson-Laird, P., 1980. Mental Models in Cognitive Science. Cognitive Science, 4(1):71-115. - https://doi.org/10.1207/s15516709cog0401_4
Kotseruba, I. and Tsotsos, J., 2020. 40 years of cognitive architectures: core cognitive abilities and practical applications. Artificial Intelligence Review, (53):17-94. - https://doi.org/10.1007/s10462-018-9646-y
Langley, P. et al., 2009. Cognitive architectures: Research issues and challenges. Cognitive Systems Research, 10(2):141-160. - https://doi.org/10.1016/j.cogsys.2006.07.004
Manzano, M., 1999. Model Theory. Oxford University Press.
Merrick, K., 2017. Value systems for develpmental cognitive robotics: A survey. Cognitive Systems Research, 41:38 - 55. - https://doi.org/10.1016/j.cogsys.2016.08.001
Miguel-Tomé, S., 2006. Principios matemáticos del pensamiento natural: Teoría cognitiva de condiciones de verdad. Gráficas Quintanilla.
Miguel-Tomé, S., 2017. Principios matemáticos del comportamiento natural. Ph.D. thesis, Universidad de Salamanca.
Miguel-Tomé, S., 2018a. Decision-making processes in the Cognitive Theory of True Conditions. ArXiv:1803.02476.
Miguel-Tomé, S., 2018b. Multi-optional Many-sorted Past Present Future structures and its description. ArXiv:1801.08212.
Miguel-Tomé, S., 2018c. Navigation through unknown and dynamic open spaces using topological notions. Connection Science, 30(2):160-185. - https://doi.org/10.1080/09540091.2016.1277691
Miller, G., 1956. The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. Psychological Review, 63(2):81-97. - https://doi.org/10.1037/h0043158
Mira-Mira, J. and García-Delgado, A., 2007. On how the computational paradigm can help us to model and interpret the neural function. Nat. Comput., 6(3):211-240. - https://doi.org/10.1007/s11047-006-9008-6
Mueller, E., 2015. Commonsense Reasoning: An Event Calculus Based Approach. Morgan Kaufmann, 2nd edition edition. - https://doi.org/10.1016/B978-0-12-801416-5.00002-4
Newell, A., 1973. You can't play 20 questions with nature and win. In Visual Information Processing, pages 283-308. Academic Press. - https://doi.org/10.1016/B978-0-12-170150-5.50012-3
Newell, A., 1990. Unified theories of cognition. Harvard University Press.
Pezzulo, G. et al., 2013. Computational Grounded Cognition: a new alliance between grounded cognition and computational modeling. Frontiers in Psychology, 3:612. - https://doi.org/10.3389/fpsyg.2012.00612
Samsonovich, A., 2010. Toward a unified catalog of implemented cognitive architectures. In Proceeding of the 2010 conference on biologically inspired cognitive architectures, pages 195-244.
Sescousse, G. et al., 2013. Processing of primary and secondary rewards: A quantitative meta-analysis and review of human functional neuroimaging studies. Neuroscience & Biobehavioral Reviews, 37(4):681 - 696. - https://doi.org/10.1016/j.neubiorev.2013.02.002
Targon, V., 2016. Learning the Semantics of Notational Systems with a Semiotic Cognitive Automaton. Cognitive Computation, 8(4):555-576. - https://doi.org/10.1007/s12559-015-9378-0
Thielscher, M., 2005. Reasoning Robots:The Art and Science of Programming Robotic Agents. Springer Netherlands.
Wang, P., 2005. Experience-grounded semantics: a theory for intelligent systems. Cognitive Systems Research, 6(4):282-302. - https://doi.org/10.1016/j.cogsys.2004.08.003
Wang, P., 2009. Analogy in a general-purpose reasoning system. Cognitive Systems Research, 10(3):286-296. - https://doi.org/10.1016/j.cogsys.2008.09.003
Barsalou, L., 2010. Grounded Cognition: Past, Present, and Future. Topics in Cognitive Science, 2(4):716-724. Brachman, R. and Levesque, H., 2004. Knowledge Representation and Reasoning. Morgan Kaufmann. - https://doi.org/10.1111/j.1756-8765.2010.01115.x
Davidson, D., 1967. Truth and Meaning. Synthese, 17(3):304-323. Davidson, D., 2005. Truth and Predication. Harvard University Press. - https://doi.org/10.1007/BF00485035
Gödel, K., 1931. Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I. - https://doi.org/10.1007/BF01700692
Monatshefte für Mathematik und Physik, 38(1):173-198.
Jacques, P. et al., 2018. Remembering and imagining alternative versions of the personal past. Neuropsychologia, 110:170-179. - https://doi.org/10.1016/j.neuropsychologia.2017.06.015
Johnson-Laird, P., 1980. Mental Models in Cognitive Science. Cognitive Science, 4(1):71-115. - https://doi.org/10.1207/s15516709cog0401_4
Kotseruba, I. and Tsotsos, J., 2020. 40 years of cognitive architectures: core cognitive abilities and practical applications. Artificial Intelligence Review, (53):17-94. - https://doi.org/10.1007/s10462-018-9646-y
Langley, P. et al., 2009. Cognitive architectures: Research issues and challenges. Cognitive Systems Research, 10(2):141-160. - https://doi.org/10.1016/j.cogsys.2006.07.004
Manzano, M., 1999. Model Theory. Oxford University Press.
Merrick, K., 2017. Value systems for develpmental cognitive robotics: A survey. Cognitive Systems Research, 41:38 - 55. - https://doi.org/10.1016/j.cogsys.2016.08.001
Miguel-Tomé, S., 2006. Principios matemáticos del pensamiento natural: Teoría cognitiva de condiciones de verdad. Gráficas Quintanilla.
Miguel-Tomé, S., 2017. Principios matemáticos del comportamiento natural. Ph.D. thesis, Universidad de Salamanca.
Miguel-Tomé, S., 2018a. Decision-making processes in the Cognitive Theory of True Conditions. ArXiv:1803.02476.
Miguel-Tomé, S., 2018b. Multi-optional Many-sorted Past Present Future structures and its description. ArXiv:1801.08212.
Miguel-Tomé, S., 2018c. Navigation through unknown and dynamic open spaces using topological notions. Connection Science, 30(2):160-185. - https://doi.org/10.1080/09540091.2016.1277691
Miller, G., 1956. The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. Psychological Review, 63(2):81-97. - https://doi.org/10.1037/h0043158
Mira-Mira, J. and García-Delgado, A., 2007. On how the computational paradigm can help us to model and interpret the neural function. Nat. Comput., 6(3):211-240. - https://doi.org/10.1007/s11047-006-9008-6
Mueller, E., 2015. Commonsense Reasoning: An Event Calculus Based Approach. Morgan Kaufmann, 2nd edition edition. - https://doi.org/10.1016/B978-0-12-801416-5.00002-4
Newell, A., 1973. You can't play 20 questions with nature and win. In Visual Information Processing, pages 283-308. Academic Press. - https://doi.org/10.1016/B978-0-12-170150-5.50012-3
Newell, A., 1990. Unified theories of cognition. Harvard University Press.
Pezzulo, G. et al., 2013. Computational Grounded Cognition: a new alliance between grounded cognition and computational modeling. Frontiers in Psychology, 3:612. - https://doi.org/10.3389/fpsyg.2012.00612
Samsonovich, A., 2010. Toward a unified catalog of implemented cognitive architectures. In Proceeding of the 2010 conference on biologically inspired cognitive architectures, pages 195-244.
Sescousse, G. et al., 2013. Processing of primary and secondary rewards: A quantitative meta-analysis and review of human functional neuroimaging studies. Neuroscience & Biobehavioral Reviews, 37(4):681 - 696. - https://doi.org/10.1016/j.neubiorev.2013.02.002
Targon, V., 2016. Learning the Semantics of Notational Systems with a Semiotic Cognitive Automaton. Cognitive Computation, 8(4):555-576. - https://doi.org/10.1007/s12559-015-9378-0
Thielscher, M., 2005. Reasoning Robots:The Art and Science of Programming Robotic Agents. Springer Netherlands.
Wang, P., 2005. Experience-grounded semantics: a theory for intelligent systems. Cognitive Systems Research, 6(4):282-302. - https://doi.org/10.1016/j.cogsys.2004.08.003
Wang, P., 2009. Analogy in a general-purpose reasoning system. Cognitive Systems Research, 10(3):286-296. - https://doi.org/10.1016/j.cogsys.2008.09.003
Miguel Tomé, S. (2020). Towards a model-theoretic framework for describing the semantic aspects of cognitive processes. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8(4), 83–96. https://doi.org/10.14201/ADCAIJ2019848396
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