280 search results - page 31 / 56 » Planning for Markov Decision Processes with Sparse Stochasti... |
AAAI
2010
14 years 11 months ago
2010
Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
139
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PKDD
2010
Springer
14 years 7 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
150
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CLIMA
2011
13 years 9 months ago
2011
Multi-agent systems are an increasingly important software paradigm and in many of its applications agents cooperate to achieve a particular goal. This requires the design of effi...
119
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IJRR
2010
14 years 8 months ago
2010
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
ATAL
2008
Springer
14 years 12 months ago
2008
Springer
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...