827 search results - page 22 / 166 » Variational methods for Reinforcement Learning |
107
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ECCV
2008
Springer
16 years 2 months ago
2008
Springer
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
107
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TSMC
2008
15 years 11 days ago
2008
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
131
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AAAI
2006
15 years 1 months ago
2006
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
125
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AAAI
2012
13 years 2 months ago
2012
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
128
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IWLCS
2005
Springer
15 years 6 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 ...