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Artificial intelligence and human thinking

Published: 16 July 2011 Publication History

Abstract

Research in AI has built upon the tools and techniques of many different disciplines, including formal logic, probability theory, decision theory, management science, linguistics and philosophy. However, the application of these disciplines in AI has necessitated the development of many enhancements and extensions. Among the most powerful of these are the methods of computational logic.
I will argue that computational logic, embedded in an agent cycle, combines and improves upon both traditional logic and classical decision theory. I will also argue that many of its methods can be used, not only in AI, but also in ordinary life, to help people improve their own human intelligence without the assistance of computers.

References

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Kurt A. Carlson, Chris Janiszewski, Ralph L. Keeney, David H. Krantz, Howard C. Kunreuther, Mary Frances Luce, J. Edward Russo, Stijn M. J. van Osselaer and Detlof von Winterfeldt. A theoretical framework for goal-based choice and for prescriptive analysis. Marketing Letters, 19(3-4):241-254.
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John Hammond, Ralph Keeney and Howard Raiffa. Smart Choices - A practical guide to making better decisions. Harvard Business School Press.
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Daniel Kahneman and Shane Frederick. Representativeness revisited: attribute substitution in intuitive judgment. In Heuristics and Biases - The Psychology of Intuitive Judgement. Cambridge University Press.
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Ralph Keeney. Value-focused thinking: a path to creative decision-making. Harvard University Press.
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Robert Kowalski. A proof procedure using connection graphs, JACM, 22(4):572-595.
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Robert Kowalski. Logic for Problem Solving. North Holland Elsevier (1979). Also at http://www.doc.ic.ac.uk/~rak/.
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Robert Kowalski. Computational Logic and Human Thinking - How to be Artificially Intelligent. Cambridge University Press.
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Pattie Maes. Situated agents can have goals. Robot. Autonomous Syst. 6(1-2):49-70.
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David Poole. The independent choice logic for modeling multiple agents under uncertainty. Artificial Intelligence, 94:7-56.
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Daniel Sperber, and Deidre Wilson. Relevance. Blackwell, Oxford.
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Joseph Williams. Style: Toward Clarity and Grace. University of Chicago Press.

Cited By

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  • (2011)Why we need evolutionary semanticsProceedings of the 34th Annual German conference on Advances in artificial intelligence10.5555/2051037.2051039(14-25)Online publication date: 4-Oct-2011
  1. Artificial intelligence and human thinking

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    Published In

    cover image Guide Proceedings
    IJCAI'11: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
    July 2011
    704 pages
    ISBN:9781577355137

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    • The International Joint Conferences on Artificial Intelligence, Inc. (IJCAI)

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    AAAI Press

    Publication History

    Published: 16 July 2011

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    • (2011)Why we need evolutionary semanticsProceedings of the 34th Annual German conference on Advances in artificial intelligence10.5555/2051037.2051039(14-25)Online publication date: 4-Oct-2011

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