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X-WR-CALNAME:Policy and Heuristic-Guided Tree Search Algorithms
X-WR-TIMEZONE:America/Los_Angeles
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DTSTART:20070311T020000
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DTSTART:20071104T020000
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UID:2021-05-03-levi-lelis@cml.ics.uci.edu
DTSTAMP:20210503T000000Z
SEQUENCE:57690
DTSTART;TZID=America/Los_Angeles:20210503T130000
DTEND;TZID=America/Los_Angeles:20210503T140000
SUMMARY:[CML Seminar] Levi Lelis: Policy and Heuristic-Guided Tree Search A
 lgorithms
LOCATION:Online (live stream)
DESCRIPTION:Levi Lelis\, Assistant Professor\, Department of Computer Scien
 ce\, University of Alberta\n\nTitle: Policy and Heuristic-Guided Tree Sear
 ch Algorithms\n\nAbstract: In this talk I describe two tree search algorit
 hms that use a policy to guide the search. I start with Levin tree search 
 (LTS)\, a best-first search algorithm with guarantees on the number of nod
 es it needs to expand\, based on the quality of the policy it employs. I t
 hen describe Policy-Guided Heuristic Search (PHS)\, which uses both a poli
 cy and a heuristic function to guide the search\, with guarantees based on
  the quality of both. Empirical results show that LTS and PHS compare favo
 rably with A*\, Weighted A*\, Greedy Best-First Search\, and PUCT on singl
 e-agent shortest-path problems.\n\nhttps://cml.ics.uci.edu/seminars/2021-0
 5-03-levi-lelis
X-ALT-DESC;FMTTYPE=text/html:<html><body><b>Levi Lelis</b>\, Assistant Prof
 essor\, Department of Computer Science\, University of Alberta<br><br><b>T
 itle:</b> Policy and Heuristic-Guided Tree Search Algorithms<br><br><b>Abs
 tract:</b> In this talk I describe two tree search algorithms that use a p
 olicy to guide the search. I start with Levin tree search (LTS)\, a best-f
 irst search algorithm with guarantees on the number of nodes it needs to e
 xpand\, based on the quality of the policy it employs. I then describe Pol
 icy-Guided Heuristic Search (PHS)\, which uses both a policy and a heurist
 ic function to guide the search\, with guarantees based on the quality of 
 both. Empirical results show that LTS and PHS compare favorably with A*\, 
 Weighted A*\, Greedy Best-First Search\, and PUCT on single-agent shortest
 -path problems.<br><br><a href="https://cml.ics.uci.edu/seminars/2021-05-0
 3-levi-lelis">https://cml.ics.uci.edu/seminars/2021-05-03-levi-lelis</a></
 body></html>
URL:https://cml.ics.uci.edu/seminars/2021-05-03-levi-lelis
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