486 search results - page 26 / 98 » A Bayesian Framework for Reinforcement Learning |
ECML
2004
Springer
14 years 2 months ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
ECAI
2010
Springer
13 years 9 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, ...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
ECAI
2008
Springer
13 years 10 months ago
2008
Springer
Focused crawlers are programs that wander in the Web, using its graph structure, and gather pages that belong to a specific topic. The most critical task in Focused Crawling is the...