Role of Logic in Cognitive Science

• Autorzy: Paweł Balcerak
• Języki publikacji: EN

Abstrakty

EN

In their work McCulloch and Pitts describe an idea of representing all of nervous activity in terms of propositional logic. This idea was quickly challenged. One of reasons for this challenge was rising believe that logic is unable to describe most of human cognitive processes. In this paper we will analyse premises of original McCulloch and Pitts proposition. Following that, we will ask about ability of symbolic (logical) systems to represent human cognition. We will finish by analysing relation between symbolic and subsymbolic computing, in hope of bridging the gap between the two. (original abstract)

Słowa kluczowe

EN

Logic; Neural networks; Human mind

PL

Logika; Sieci neuronowe; Umysł ludzki

• Czasopismo: Studia Humana
• Rocznik: 2018
• Tom: 7(1)
• Strony: 21--30

Twórcy

autor

Paweł Balcerak

• University of Rzeszów, Poland

Bibliografia

• 1. Anderson, J. R. & C. Lebiere. The Atomic Components of Thought, Mahwah, NJ: Erlbaum, 1998.
• 2. Balkenius, C. & P. Gärdenfors. Nonmonotonic inferences in neural networks, In J. Allen, R. Fikes, & W. Sandewall (eds.), Principle of Knowledge Representation and Reasoning, Morgan Kaufmann, 1991, pp. 32-39.
• 3. Davidson, D. Inquiries into truth and interpretation, Oxford: Clarendon Press, 1984.
• 4. Dennett, D. Brainstorms, Cambridge, MA: MIT Press, 1978.
• 5. Evans, J. St. B.T. In two minds: Dual-process accounts of reasoning, Trends in Cognitive Sciences, 7(10), 2003, pp. 454-459.
• 6. Fodor, J. A. & Z. Pylyshyn. Connectionism and cognitive architecture: A critical analysis, Cognition, 28, 1988, pp. 3-71.
• 7. Gärdenfors, P. Conceptual Spaces: The Geometry of Thought, Cambridge, MA: MIT Press, 2000.
• 8. Griggs, R. A. & J. R. Cox. The elusive thematic-materials effect in Wason's selection task, British Journal of Psychology, 73, 1982, pp. 407-420.
• 9. Hölldobler, S. & Y. Kalinke. Toward a new massively parallel computational model for logic programming, In Proc. Workshop on Combining Symbolic and Connectionist Processing, ECAI-94, Amsterdam, 1994.
• 10. Immerman, N. Descriptive complexity, New York: Springer Verlag, 1999.
• 11. Johnson-Laird, P. N., Legrenzi, P., & M. S., Legrenzi. Reasoning and a sense of reality, British Journal of Psychology, 63, 1972, pp. 395-400.
• 12. Kleene, S. Representation of events in nerve nets and finite automata, In C. Shannon & J. McCarthy (eds.), Automata Studies, 1956, pp. 3-42.
• 13. Leitgeb, H. Nonmonotonic reasoning by inhibition nets, Artificial Intelligence, 128 (1-2), 2001, pp. 161-201.
• 14. Leitgeb, H. Nonmonotonic reasoning by inhibition nets II, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11 (2 (Supplement)), 2003, pp. 105-135.
• 15. Leitgeb, H. Interpreted dynamical systems and qualitative laws: From neural networks to evolutionary systems, Synthese, 146, 2005, pp. 189-202.
• 16. McCulloch, W. S. & W. H. Pitts. A Logical Calculus Immanent in Nervous Activity, Bulletin of Mathematical Biophysics, 5, 1943, pp. 115-133.
• 17. Oaksford, M. & M. Chater. The Probabilistic Mind: Prospects for Bayesian Cognitive Science, Oxford University Press, 2008.
• 18. Pylyshyn, Z. W. (ed.) The Robot's Dilemma: The Frame Problem in Artificial Intelligence, Ablex, 1987.
• 19. Quine, W. V. O. Word and object, Cambridge, MA: MIT Press, 1960.
• 20. Shoham, Y. A Semantical Approach to Nonmonotonic Logics, In M. L. Ginsberg, (ed.), Readings in Non-Monotonic Reasoning, Los Altos, CA: Morgan Kaufmann, 1987, pp. 227-249.
• 21. Stenning, K. & M. van Lambalgen. Human Reasoning and Cognitive Science, Los Altos, CA: MIT Press, 2008.
• 22. Turing, A. M. Computing machinery and intelligence, Mind, 59, 1950, pp. 433-460.
• 23. Wason, P. C. Reasoning about a rule, Quarterly Journal of Experimental Psychology, 20, 1968, pp. 273-281.
• 24. Wason, P. C. & D. Shapiro. Natural and contrived experience in a reasoning problem, Quarterly Journal of Experimental Psychology, 23, 1971, pp. 63-71.
• 25. Wermter, S. & R. Sun (ed.) Hybrid Neural Systems, Berlin: Springer Verlag, 2000.

Identyfikatory

DOI

10.2478/sh-2018-0002