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Date: Tue, 10 Dec 1996 15:18:00 GMTServer: NCSA/1.4.2Content-type: text/htmlLast-modified: Wed, 28 Feb 1996 00:55:40 GMTContent-length: 3146<html><head><title>Probabilistic Planning</title></head><body><h3>Probabilistic Planning</h3>Adapting classical planning algorithmsto deal with uncertainty about the world state and the effects of actions:    <ul>       <li> The <!WA0><a href="http://www.cs.washington.edu/research/projects/ai/www/bur.html">Buridan planner </a> is a first          attempt at a probabilitic planner, and explores issues          like what the action and state representation should          be, and how the problem of <i> evaluating </i> a partially          generated plan interacts with <i> generating </i> a plan.          Buridan assumes the agent will get no additional information          about the world at execution time.       <li> The Conditional Buridan planner is an extension that allows        actions to provide <i> information </i> about the world as well         as <i> change </i> the world.   This is joint work with         <!WA1><A HREF="http://www.cs.washington.edu/people/faculty/weld.html"> Dan Weld </a>                 and         <!WA2><A HREF="http://www.cs.washington.edu/homes/ddraper/">            Denise Draper</a>.         Recent CBuridan papers include:            <ul>              <li> <!WA3><A HREF="ftp://ftp.cs.washington.edu/pub/ai/cbur-aips94.ps.Z">                     <i> Probabilistic Planning with Information Gathering and Contingent                      Execution </i> </a> which appears in the AIPS94 proceedings.              <li> <!WA4><A HREF="ftp://ftp.cs.washington.edu/pub/ai/cbur-uai94.ps.Z">                     <i> A Probabilistic Model of Action for Least-Commitment Planning                            with Information Gathering  </i> </a>                        which appears in the AIPS94 proceedings.              <li> <!WA5><A HREF="ftp://ftp.cs.washington.edu/tr/1993/12/UW-CSE-93-12-04.PS.Z">                     <i> Probabilistic Planning with Information Gathering and                           Contingent Execution</i></a>, a longer tech report describing                           the same material.            </ul>      <li> Also see information on the UWL language, which is        a symbolic (non-probabilistic) approach to planning with        information-producing actions and conditionals.        <!WA6><A HREF="ftp://ftp.cs.washington.edu/pub/ai/uwl-kr92.ps.Z">             <i> An Approach to Planning with Incomplete Information </i>        </a>           by             <!WA7><A HREF="http://www.cs.washington.edu/people/faculty/etzioni.html">                Etzioni            </a>,            <!WA8><A HREF="http://www.cs.washington.edu/people/faculty/hanks.html">                Hanks            </a>,            <!WA9><A HREF="http://www.cs.washington.edu/people/faculty/weld.html">                 Weld            </a>,            <!WA10><A HREF="http://www.cs.washington.edu/homes/ddraper">                 Draper            </a>,            <!WA11><A HREF="http://www.cs.washington.edu/homes/neal">                 Lesh</a>, and            <!WA12><A HREF="http://www.cs.washington.edu/homes/mikew"> Williamson</a>.     </ul><address> hanks@cs.washington.edu</address> </body></html>

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