250 search results - page 12 / 50 » Learning action effects in partially observable domains |
AAAI
2011
13 years 9 months ago
2011
Automated agents for electricity markets, social networks, and other distributed networks must repeatedly interact with other intelligent agents, often without observing associate...
100
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NIPS
2007
14 years 11 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
95
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ATAL
2010
Springer
14 years 10 months ago
2010
Springer
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
ROBOCUP
2007
Springer
15 years 3 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
ICCBR
2005
Springer
15 years 3 months ago
2005
Springer
Automatic case elicitation (ACE) is a learning technique in which a case-based reasoning system acquires knowledge automatically from scratch through repeated real-time trial and e...