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  1. The independent choice logic for modelling multiple agents under uncertainty.David Poole - 1997 - Artificial Intelligence 94 (1-2):7-56.
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  • (2 other versions)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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  • Perception as Abduction: Turning Sensor Data Into Meaningful Representation.Murray Shanahan - 2005 - Cognitive Science 29 (1):103-134.
    This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby low‐level sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, top‐down information flow, active perception, attention, and sensor fusion in a unifying framework. In addition, a number of themes are identified that are common to both the engineer concerned with developing a rigorous theory of perception, such as the one on (...)
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  • A theory of abstraction.Fausto Giunchiglia & Toby Walsh - 1992 - Artificial Intelligence 57 (2-3):323-389.
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  • Belief functions on distributive lattices.Chunlai Zhou - 2013 - Artificial Intelligence 201 (C):1-31.
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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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  • Open Information Systems Semantics for distributed artificial intelligence.Carl Hewitt - 1991 - Artificial Intelligence 47 (1-3):79-106.
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  • Explaining Emotions.Paul O'Rorke & Andrew Ortony - 1994 - Cognitive Science 18 (2):283-323.
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  • Tractable reasoning via approximation.Marco Schaerf & Marco Cadoli - 1995 - Artificial Intelligence 74 (2):249-310.
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  • Rigor mortis: A response to Nilsson's 'logic and artificial intelligence'.Lawrence Birnbaum - 1991 - Artificial Intelligence 47 (1-3):57-78.
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  • Towards Fuzzy Linguistic Logic Programming.Clemente Rubio-Manzano & Pascual Julian-Iranzo - 2014 - Archives for the Philosophy and History of Soft Computing 2014 (2).
    Knowledge representation is one of the central concepts in Artificial Intelligence. It is very common that knowledge about a field is expressed in natural language. Therefore, most of the times, knowledge representation using a logic programming language derives into a translation problem. This translation consists in the formalization of the statements, belonging to the knowledge level, which are converted into formulas of the so called symbolic level. Knowledge may be imprecise or vague and, in order to deal with vagueness using (...)
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  • 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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  • 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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  • Let's plan it deductively!W. Bibel - 1998 - Artificial Intelligence 103 (1-2):183-208.
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