David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Cambridge University Press (1994)
Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject, and formalising within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the main theories about uncertain reasoning, so the book can serve as a textbook for beginners or as a starting point for further basic research into the subject. It will be welcomed by graduate students and research workers in logic, philosophy, and computer science as a textbook for beginners, a starting point for further basic research into the subject, and not least, an account of how mathematics and artificial intelligence can complement and enrich each other.
|Keywords||Logic, Symbolic and mathematical Uncertainty Reasoning Incertitude Raisonnement|
|Categories||categorize this paper)|
|Buy the book||$54.87 new (9% off) $57.63 used (4% off) $59.99 direct from Amazon Amazon page|
|Call number||QA9.P28 1994|
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Citations of this work BETA
Igor Douven, Leon Horsten & Jan-Willem Romeijn (2010). Probabilist antirealism. Pacific Philosophical Quarterly 91 (1):38-63.
Gerhard Schurz & Paul D. Thorn (2012). REWARD VERSUS RISK IN UNCERTAIN INFERENCE: THEOREMS AND SIMULATIONS. Review of Symbolic Logic 5 (4):574-612.
J. Paris & A. Vencovská (2011). Symmetry's End? Erkenntnis 74 (1):53-67.
Colin Howson (2007). Logic with Numbers. Synthese 156 (3):491-512.
Emil Weydert (2012). Conditional Ranking Revision. Journal of Philosophical Logic 41 (1):237-271.
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