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Date: Tue, 10 Dec 1996 15:17:50 GMTServer: NCSA/1.4.2Content-type: text/htmlLast-modified: Wed, 28 Feb 1996 00:56:12 GMTContent-length: 2050<html><head><title>Utility Models</title></head><body><h3>Utility Models and Goals</h3>A goal is a restrictive measure of how good a plan is. Preference or utility models can be arbitrarily expressive about plan quality, but how do you use them to generate plans? <ul> <li> Work with <!WA0><a href="http://www.cs.uwm.edu/faculty/haddawy/index.html"> Peter Haddawy</a> explores the form of utility models that incorporate traditional symbolic goals with information about temporal deadlines, partial satisfaction, and resource consumption. Publications include: <ul> <li> <i> Issues in Decision-Theoretic Planning: Symbolic Goals and Numeric Utilities</i>, which appears in the Proceedings of the 1990 DARPA Planning Workshop, <li> <i> Representations for Decision-Theoretic Planning: Utility Functions for Deadline Goals</i> which appears in the KR92 Proceedings, <li> <!WA1><A HREF="ftp://ftp.cs.washington.edu/pub/ai/haddawy-hanks-aij-submission.ps.Z"> <i> Utility Models for Goal-Directed Decision-Theoretic Planners</i></a>, which is under review for journal publication. </ul> </ul> <li> Work with <!WA2><A HREF="http://www.cs.washington.edu/homes/mikew"> Mike Williamson</a> explores how these formal models can be integrated with a least-commitment planning algorithms. The result is PYRRHUS, a planner that generates optimal plans in a delivery-truck domain (using the <!WA3><a href="http://www.cs.washington.edu/homes/hanks/projects/testbeds.html"> Truckworld testbed</a>. See <!WA4><A HREF="ftp://ftp.cs.washington.edu/pub/ai/williamson-hanks-pyrrhus-aips94.ps.Z"> <i> Optimal Planning with a Goal-Directed Utility Model</i></a>, which appeared in the AIPS94 proceedings. </ul> </ul><address> hanks@cs.washington.edu</address> </body></html>⌨️ 快捷键说明
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