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Stochastic control / Multivariate statistics / Partially observable Markov decision process / Statistical theory / Automated planning and scheduling / Principal component analysis / Reinforcement learning / Dimension reduction / Markov decision process / Statistics / Dynamic programming / Markov processes


Journal of Artificial Intelligence Research[removed]Submitted 05/04; published[removed]Finding Approximate POMDP Solutions Through Belief Compression
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Document Date: 2005-01-30 19:00:16

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City

Pittsburgh / Cambridge / /

Company

Cox / Russell / /

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Facility

GNU Scientific Library / Carnegie Mellon University / Stanford University / Massachusetts Institute of Technology / Artificial Intelligence Laboratory / /

IndustryTerm

travel distance / statistical dimensionality reduction algorithms / dialogue systems / approximate solutions / physical systems / /

MarketIndex

set 500 / /

OperatingSystem

GNU / /

Organization

AI Access Foundation / Stanford University / Carnegie Mellon University / Massachusetts Institute of Technology / School of Computer Science Pittsburgh / /

Person

Geoffrey Gordon / Max Prob / Sebastian Thrun / Figure / Nicholas Roy / /

Position

motion planner / controller in Figure / conventional motion planner / hand-coded controller / planner / Conventional controller / controller / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Journal of Artificial Intelligence Research / /

SportsLeague

Stanford University / /

Technology

laser / Golub-Reinsche algorithm / artificial intelligence / 01/05 Finding Approximate POMDP Solutions Through Belief Compression Nicholas Roy nickroy@mit.edu Massachusetts Institute of Technology / statistical dimensionality reduction algorithms / /

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