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<i class="">Computer Science Seminar</i>
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<div class=""><b class="">Andrew Drucker</b></div>
<div class=""><b class="">Assistant Professor, Department of Computer Science</b></div>
<div class=""><b class="">University of Chicago</b></div>
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<div class=""><b class="">Friday September 30th </b></div>
<div class=""><b class="">2:30pm-3:30pm</b></div>
<div class=""><b class="">In Person: John Crerar Library 390</b></div>
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<div class=""><b class="">Title: </b><b class="">A</b><b class="">ccelerating Search for Decision-Making Under Uncertainty</b></div>
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<div class=""><b class="">Abstract: </b>I will discuss my research in CS theory, with a focus on <i class="">decision-making under uncertainty</i>.<span class="gmail-Apple-converted-space"> </span>A broad variety of decision-making tasks can be modeled as
“games against Nature”, in which a player alternates moves with an opponent (“Nature”) who plays randomly. <span class="gmail-Apple-converted-space"> </span></div>
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For general binary-move games, I have provided an algorithm yielding rigorous exponential computational savings over brute-force search—with no assumption of bounded state-space.<span class="gmail-Apple-converted-space"> </span>This provides, for the first
time, a search technique in this setting of power comparable to alpha/beta-style pruning for games against adversarial opponents.<span class="gmail-Apple-converted-space"> </span>I will discuss the ideas involved, which are new and much more subtle than in
the adversarial setting, and which hold promise for further work.
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<div class="">Holly Santos<br class="">
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<div>Executive Assistant to Michael J. Franklin, Chairman<br class="">
Department of Computer Science<br class="">
The University of Chicago<br class="">
5730 S Ellis Ave-217 Chicago, IL 60637<br class="">
P: 773-834-8977<br class="">
<a href="mailto:hsantos@uchicago.edu" class="">hsantos@uchicago.edu</a></div>
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