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  1. The assumptions on knowledge and resources in models of rationality.Pei Wang - 2011 - International Journal of Machine Consciousness 3 (01):193-218.
    Intelligence can be understood as a form of rationality, in the sense that an intelligent system does its best when its knowledge and resources are insufficient with respect to the problems to be solved. The traditional models of rationality typically assume some form of sufficiency of knowledge and resources, so cannot solve many theoretical and practical problems in Artificial Intelligence (AI). New models based on the Assumption of Insufficient Knowledge and Resources (AIKR) cannot be obtained by minor revisions or extensions (...)
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  • The tripartite model of representation.Peter Slezak - 2002 - Philosophical Psychology 15 (3):239-270.
    Robert Cummins [(1996) Representations, targets and attitudes, Cambridge, MA: Bradford/MIT, p. 1] has characterized the vexed problem of mental representation as "the topic in the philosophy of mind for some time now." This remark is something of an understatement. The same topic was central to the famous controversy between Nicolas Malebranche and Antoine Arnauld in the 17th century and remained central to the entire philosophical tradition of "ideas" in the writings of Locke, Berkeley, Hume, Reid and Kant. However, the scholarly, (...)
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  • Explaining Emotions.Paul O'Rorke & Andrew Ortony - 1994 - Cognitive Science 18 (2):283-323.
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  • Foundations of AI: The big issues.David Kirsh - 1991 - Artificial Intelligence 47 (1-3):3-30.
    The objective of research in the foundations of Al is to explore such basic questions as: What is a theory in Al? What are the most abstract assumptions underlying the competing visions of intelligence? What are the basic arguments for and against each assumption? In this essay I discuss five foundational issues: (1) Core Al is the study of conceptualization and should begin with knowledge level theories. (2) Cognition can be studied as a disembodied process without solving the symbol grounding (...)
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  • AI and representation: A study of a rhetorical context for legitimacy. [REVIEW]Lynette A. C. Hunter - 1993 - AI and Society 7 (3):185-207.
    Theoretical commentaries on AI often operate as a metadiscourse on the way in which science represents itself to a wider public. The sciences and humanities do the same kind of work but in different fields that encourage them to talk about their work differently: science refers to a natural world that does not talk back, and the humanities refer continually to a world with communicative people in it. This paper suggests that much AI commentary is misconceived because it models itself (...)
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  • On isomorphic formalisations.Routen Tom - 1996 - Artificial Intelligence and Law 4 (2):113-132.
    Previous research into the formalisation of statute law identified a number of uses of language which posed problems for formalisation. A previous paper argued that these uses establish the requirement that a formalisation be isomorphic, but noted that this has odd consequences. This paper expands on what these consequences are and argues that they undermine the very idea of formalisation. Therefore, the whole argument constitutes a reductio ad absurdum of the idea of formalising statute law. The paper provides reasons why (...)
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