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» Reinforcement Learning Estimation of Distribution Algorithm
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ILP
2007
Springer
15 years 5 months ago
Building Relational World Models for Reinforcement Learning
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
105
Voted
CEC
2009
IEEE
15 years 6 months ago
Structure learning and optimisation in a Markov-network based estimation of distribution algorithm
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
Alexander E. I. Brownlee, John A. W. McCall, Siddh...
ICAC
2009
IEEE
14 years 9 months ago
Using distributed w-learning for multi-policy optimization in decentralized autonomic systems
Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
Ivana Dusparic, Vinny Cahill
91
Voted
IJRR
2008
186views more  IJRR 2008»
14 years 11 months ago
Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Paulina Varshavskaya, Leslie Pack Kaelbling, Danie...
CORR
2010
Springer
105views Education» more  CORR 2010»
14 years 10 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...