231 search results - page 29 / 47 » Active Learning in Partially Observable Markov Decision Proc... |
AAAI
2010
13 years 10 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...
ATAL
2008
Springer
13 years 10 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...
AAAI
2012
11 years 11 months ago
2012
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
JSAC
2008
13 years 7 months ago
2008
In this paper we design a cognitive radio that can coexist with multiple parallel WLAN channels while abiding by an interference constraint. The interaction between both systems is...
AAAI
2007
13 years 11 months ago
2007
Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...