92 search results - page 9 / 19 » Acting Optimally in Partially Observable Stochastic Domains |
145
Voted
GLOBECOM
2009
IEEE
14 years 11 months ago
2009
IEEE
Abstract--We consider a set of multicast sources, each multicasting a finite amount of data to its corresponding destinations. The objective is to minimize the time to deliver all ...
120
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ATAL
2007
Springer
15 years 8 months ago
2007
Springer
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
131
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ECAI
2010
Springer
15 years 3 months ago
2010
Springer
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
138
Voted
IJCAI
2001
15 years 3 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
134
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ATAL
2008
Springer
15 years 3 months ago
2008
Springer
Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, a...