190 search results - page 15 / 38 » Abstraction and Generalization in Reinforcement Learning: A ... |
SSDBM
2008
IEEE
14 years 2 months ago
2008
IEEE
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
ICCBR
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Acquiring adaptation knowledge for case-based reasoning systems is a challenging problem. Such knowledge is typically elicited from domain experts or extracted from the c...
SARA
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. We present The Cruncher, a simple representation framework and algorithm based on minimum description length for automatically forming an ontology of concepts from attrib...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...