Uncertainty in Artificial Intelligence
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Arguing for Decisions: A Qualitative Model of Decision Making
Blai Bonet, Hector Geffner
Abstract:
We develop a qualitative model of decision making with two aims: to describe how people make simple decisions and to enable computer programs to do the same. Current approaches based on Planning or Decisions Theory either ignore uncertainty and tradeoffs, or provide languages and algorithms that are too complex for this task. The proposed model provides a language based on rules, a semantics based on high probabilities and lexicographical preferences, and a transparent decision procedure where reasons for and against decisions interact. The model is no substitude for Decision Theory, yet for decisions that people find easy to explain it may provide an appealing alternative.
Keywords: Qualitative decision theory, arguments, planning.
Pages: 98-105
PS Link:
PDF Link: /papers/96/p98-bonet.pdf
BibTex:
@INPROCEEDINGS{Bonet96,
AUTHOR = "Blai Bonet and Hector Geffner",
TITLE = "Arguing for Decisions: A Qualitative Model of Decision Making",
BOOKTITLE = "Proceedings of the Twelfth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-96)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1996",
PAGES = "98--105"
}


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