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<article-title>Autonomous Nondeterministic Tour Guides:Improving Quality of Experience<br/>with TTD-MDPs</article-title>
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<author><a href="mailto:cantino@cc.gatech.edu"><name>Andrew S. Cantino</name></a></author>
<aff>College of Computing, Georgia Institute of Technology, Atlanta, GA</aff>

<author><a href="mailto:robertsd@cc.gatech.edu"><name>David L. Roberts</name></a></author>
<aff>College of Computing, Georgia Institute of Technology, Atlanta, GA</aff>

<author><a href="mailto:isbellg@cc.gatech.edu"><name>Charles L. Isbell</name></a></author>
<aff>College of Computing, Georgia Institute of Technology, Atlanta, GA</aff>
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<p>In this paper, we address the problem of building a system of autonomous agents for a complex environment, in our case, a museum with many visitors. Visitors may have varying preferences for types of art or may wish to visit different exhibits on multiple visits. Often, these goals conict. For example, many visitors may wish to see the museum's most popular work, but that could cause congestion, ruining the experience. Thus, our task is to build a set of agents that can satisfy their visitors' goals, while simultaneously providing high quality experiences for all.</p>
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