TY - GEN
T1 - Evidence and Belief
AU - Gilboa, Itzhak
AU - Schmeidler, David
N1 - Publisher Copyright:
Copyright © 2004, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2004
Y1 - 2004
N2 - We discuss the representation of knowledge and of belief from the viewpoint of decision theory. While the Bayesian approach enjoys general-purpose applicability and axiomatic foundations, it suffers from several drawbacks. In particular, it does not model the belief formation process, and does not relate beliefs to evidence. We survey alternative approaches, and focus on formal model of case-based prediction and case-based decisions.
AB - We discuss the representation of knowledge and of belief from the viewpoint of decision theory. While the Bayesian approach enjoys general-purpose applicability and axiomatic foundations, it suffers from several drawbacks. In particular, it does not model the belief formation process, and does not relate beliefs to evidence. We survey alternative approaches, and focus on formal model of case-based prediction and case-based decisions.
UR - http://www.scopus.com/inward/record.url?scp=85167429355&partnerID=8YFLogxK
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AN - SCOPUS:85167429355
T3 - Principles of Knowledge Representation and Reasoning: Proceedings of the 9th International Conference, KR 2004
SP - 733
EP - 734
BT - Principles of Knowledge Representation and Reasoning
PB - AAAI press
T2 - 9th International Conference on Principles of Knowledge Representation and Reasoning, KR 2004
Y2 - 2 June 2004 through 5 June 2004
ER -