Uncertainty in Artificial Intelligence
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Exploiting the Rule Structure for Decision Making within the Independent Choice Logic
David Poole
Abstract:
This paper introduces the independent choice logic, and in particular the "single agent with nature" instance of the independent choice logic, namely ICLdt. This is a logical framework for decision making uncertainty that extends both logic programming and stochastic models such as influence diagrams. This paper shows how the representation of a decision problem within the independent choice logic can be exploited to cut down the combinatorics of dynamic programming. One of the main problems with influence diagram evaluation techniques is the need to optimise a decision for all values of the 'parents' of a decision variable. In this paper we show how the rule based nature of the ICLdt can be exploited so that we only make distinctions in the values of the information available for a decision that will make a difference to utility.
Keywords: Independent choice logic, influence diagrams, dynamic programming, logic programs, p
Pages: 454-463
PS Link: ftp://ftp.cs.ubc.ca/ftp/local/poole/papers/exploit.ps
PDF Link: /papers/95/p454-poole.pdf
BibTex:
@INPROCEEDINGS{Poole95,
AUTHOR = "David Poole ",
TITLE = "Exploiting the Rule Structure for Decision Making within the Independent Choice Logic",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "454--463"
}


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