2299 search results - page 126 / 460 » Inference and Learning in Planning |
164
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ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
152
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AAMAS
2005
Springer
16 years 1 days ago
2005
Springer
The ability to determine a sequence of actions in order to reach a particular goal is of utmost importance to mobile robots. One major problem with symbolic planning approaches re...
180
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COLT
2010
Springer
15 years 4 months ago
2010
Springer
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
147
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ICML
2006
IEEE
16 years 7 months ago
2006
IEEE
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
154
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ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
Over the past few years, a number of approximate inference algorithms for networked data have been put forth. We empirically compare the performance of three of the popular algori...