David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Topoi 24 (2):229-242 (2005)
The aims of this paper are threefold: To show that game-playing (GP), the discipline of Artificial Intelligence (AI) concerned with the development of automated game players, has a strong epistemological relevance within both AI and the vast area of cognitive sciences. In this context games can be seen as a way of securely reducing (segmenting) real-world complexity, thus creating the laboratory environment necessary for testing the diverse types and facets of intelligence produced by computer models. This paper aims to promote the belief that games represent an excellent tool for the project of computational psychology (CP). To underline how, despite this, GP has mainly adopted an engineering-inspired methodology and in doing so has distorted the framework of cognitive functionalism. Many successes (i.e. chess, checkers) have been achieved refusing human-like reasoning. The AI has appeared to work well despite ignoring an intrinsic motivation, that of creating an explanatory link between machines and mind. To assert that substantial improvements in GP may be obtained in the future only by renewed interest in human-inspired models of reasoning and in other cognitive studies. In fact, if we increase the complexity of games (from NP-Completeness to AI-Completeness) in order to reproduce real-life problems, computer science techniques enter an impasse. Many of AI’s recent GP experiences can be shown to validate this. The lack of consistent philosophical foundations for cognitive AI and the minimal philosophical commitment of AI investigation are two of the major reasons that play an important role in explaining why CP has been overlooked.
|Keywords||Artificial Intelligence Cheating Game Play Psychology Reason Science|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
David Marr (1982). Vision. Freeman.
Humberto R. Maturana & Francisco G. Varela (1980). Autopoiesis and Cognition the Realization of the Living.
Hubert L. Dreyfus (1972). What Computers Can't Do. Harper and Row.
Citations of this work BETA
Allan Bäck (2008). The Paper World of Bernard Suits. Journal of the Philosophy of Sport 35 (2):156-174.
Similar books and articles
Mr Peter R. Krebs, Smoke Without Fire: What Do Virtual Experiments in Cognitive Science Really Tell Us?
Morton Wagman (1991). Artificial Intelligence and Human Cognition. New York: Praeger.
Ahti-Veikko Pietarinen (2003). Games as Formal Tools Versus Games as Explanations in Logic and Science. Foundations of Science 8 (4):317-364.
Rajakishore Nath (2009). Philosophy of Artificial Intelligence: A Critique of the Mechanistic Theory of Mind. Universal Publishers.
Rom Harre (1990). Vigotsky and Artificial Intelligence: What Could Cognitive Psychology Possibly Be About? Midwest Studies in Philosophy 15 (1):389-399.
Margaret A. Boden (1989). Artificial Intelligence In Psychology: Interdisciplinary Essays. Cambridge: MIT Press.
Martin Ringle (ed.) (1979). Philosophical Perspectives in Artificial Intelligence. Humanities Press.
Joseph F. Rychlak (1991). Artificial Intelligence and Human Reason: A Teleological Critique. Columbia University Press.
Morton Wagman (ed.) (2000). Historical Dictionary of Quotations in Cognitive Science: A Treasury of Quotations in Psychology, Philosophy, and Artificial Intelligence. Greenwood Press.
Paul Thagard (1982). Artificial Intelligence, Psychology, and the Philosophy of Discovery. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:166 - 175.
Added to index2009-01-28
Total downloads59 ( #71,775 of 1,796,537 )
Recent downloads (6 months)21 ( #34,863 of 1,796,537 )
How can I increase my downloads?