Uncertainty in Artificial Intelligence
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Bayesian Interactive Decision Support for Multi-Attribute Problems with Even Swaps
Debarun Bhattacharjya, Jeffrey Kephart
Abstract:
Even swaps is a method for solving de- terministic multi-attribute decision problems where the decision maker iteratively simpli- fies the problem until the optimal alterna- tive is revealed (Hammond et al. 1998, 1999). We present a new practical decision support system that takes a Bayesian approach to guiding the even swaps process, where the system makes queries based on its beliefs about the decision makerÔ??s preferences and updates them as the interactive process un- folds. Through experiments, we show that it is possible to learn enough about the decision makerÔ??s preferences to measurably reduce the cognitive burden, i.e. the number and com- plexity of queries posed by the system.
Keywords:
Pages: 72-81
PS Link:
PDF Link: /papers/14/p72-bhattacharjya.pdf
BibTex:
@INPROCEEDINGS{Bhattacharjya14,
AUTHOR = "Debarun Bhattacharjya and Jeffrey Kephart",
TITLE = "Bayesian Interactive Decision Support for Multi-Attribute Problems with Even Swaps",
BOOKTITLE = "Proceedings of the Thirtieth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-14)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2014",
PAGES = "72--81"
}


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