226 search results - page 15 / 46 » Linear Bayesian Reinforcement Learning |
100
click to vote
NIPS
2008
15 years 1 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
AIIDE
2006
15 years 1 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
124
click to vote
IWLCS
2005
Springer
15 years 5 months ago
2005
Springer
Aiming to clarify the convergence or divergence conditions for Learning Classifier System (LCS), this paper explores: (1) an extreme condition where the reinforcement process of ...
KDD
2008
ACM
16 years 6 days ago
2008
ACM
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
106
click to vote
ECML
2004
Springer
15 years 5 months ago
2004
Springer
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...