567 search results - page 52 / 114 » Regularized Policy Iteration |
97
Voted
ICML
2001
IEEE
16 years 1 months ago
2001
IEEE
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
114
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ICML
1996
IEEE
16 years 1 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
IJCNN
2008
IEEE
15 years 7 months ago
2008
IEEE
— In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking in...
100
Voted
IJCAI
2001
15 years 1 months ago
2001
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
ICONIP
2009
14 years 10 months ago
2009
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...