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IJRR
2008
186views more  IJRR 2008»
13 years 7 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...
GECCO
2010
Springer
195views Optimization» more  GECCO 2010»
13 years 11 months ago
Improved step size adaptation for the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based...
Thomas Voß, Nikolaus Hansen, Christian Igel
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 11 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
RTCSA
1999
IEEE
13 years 12 months ago
Adaptive Data Broadcast Strategy for Transactions with Multiple Data Requests in Mobile Computing Environments
Data Broadcast in mobile environments has received much attention in recent years and a large number of algorithms proposed. However, existing work in the literature only assume a ...
Joe Chun-Hung Yuen, Edward Chan, Kam-yiu Lam