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» Variational methods for Reinforcement Learning
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ICML
1997
IEEE
14 years 8 months ago
Hierarchical Explanation-Based Reinforcement Learning
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
Prasad Tadepalli, Thomas G. Dietterich
ECAI
2008
Springer
13 years 9 months ago
A Simulation-based Approach for Solving Generalized Semi-Markov Decision Processes
Time is a crucial variable in planning and often requires special attention since it introduces a specific structure along with additional complexity, especially in the case of dec...
Emmanuel Rachelson, Gauthier Quesnel, Fréd&...
ICAI
2004
13 years 9 months ago
Action Inhibition
An explicit exploration strategy is necessary in reinforcement learning (RL) to balance the need to reduce the uncertainty associated with the expected outcome of an action and the...
Myriam Abramson
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
ICML
2002
IEEE
14 years 8 months ago
Coordinated Reinforcement Learning
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
Carlos Guestrin, Michail G. Lagoudakis, Ronald Par...