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Utility-Based Plan Recognition: An Extended Abstract (Short Paper)

Dorit Avrahami-Zilberbrand and Gal A. Kaminka. Utility-Based Plan Recognition: An Extended Abstract (Short Paper). In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-07), 2007.

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Abstract

Plan recognition is the process of inferring other agents' plans and goals based on their observable actions. Essentially all previous work in plan recognition has focused on the recognition process itself, with no regard to the use of the information in the recognizing agent. As a result, low-likelihood recognition hypotheses that may imply significant meaning to the observer, are ignored in existing work. In this paper, we present novel efficient algorithms that allows the observer to incorporate her own biases and preferences---in the form of a utility function---into the plan recognition process. This allows choosing recognition hypotheses based on their expected utility to the observer. We call this Utility-based Plan Recognition (UPR). We briefly discuss a hybrid symbolic decision-theoretic plan recognizer, and demonstrate the efficacy of this approach in an example.

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BibTeX

@InProceedings{aamas07dorit, 
author = {Dorit Avrahami-Zilberbrand and Gal A. Kaminka}, 
title = {Utility-Based Plan Recognition: An Extended Abstract (Short Paper)}, 
booktitle = AAMAS-07, 
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year = {2007}, 
  abstract = { Plan recognition is the process of inferring other agents' plans 
and goals based on their observable actions. Essentially all 
previous work in plan recognition has focused on the recognition 
process itself, with no regard to the use of the information in 
the recognizing agent. As a result, low-likelihood recognition 
hypotheses that may imply significant meaning to the observer, are 
ignored in existing work. In this paper, we present novel 
efficient algorithms that allows the observer to incorporate her 
own biases and preferences---in the form of a utility 
function---into the plan recognition process. This allows choosing 
recognition hypotheses based on their expected utility to the 
observer. We call this Utility-based Plan Recognition (UPR). We briefly discuss a hybrid symbolic 
decision-theoretic plan recognizer, and demonstrate the efficacy of this 
approach in an example. }, 
  wwwnote = {}, 
OPTeditor = {}, 
OPTvolume = {}, 
OPTnumber = {}, 
OPTseries = {}, 
OPTaddress = {}, 
OPTmonth = {}, 
OPTorganization = {}, 
OPTpublisher = {}, 
OPTnote = {}, 
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} 

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