771 search results - page 100 / 155 » Markov Decision Processes with Arbitrary Reward Processes |
164
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ATAL
2007
Springer
16 years 10 days ago
2007
Springer
A problem of planning for cooperative teams under uncertainty is a crucial one in multiagent systems. Decentralized partially observable Markov decision processes (DECPOMDPs) prov...
162
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ATAL
2006
Springer
15 years 10 months ago
2006
Springer
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
176
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ICRA
2010
IEEE
15 years 4 months ago
2010
IEEE
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
189
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CPAIOR
2008
Springer
15 years 8 months ago
2008
Springer
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
160
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NIPS
2008
15 years 7 months ago
2008
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...