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AAAI
2012
13 years 6 months ago
Kernel-Based Reinforcement Learning on Representative States
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...
Branislav Kveton, Georgios Theocharous
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 10 months ago
Transgenetic algorithm: a new evolutionary perspective for heuristics design
Transgenetic algorithms are evolutionary computing techniques based on living processes where cooperation is the main evolutionary strategy. Those processes contain the movement o...
Elizabeth Ferreira Gouvea Goldbarg, Marco Cé...
CEC
2009
IEEE
15 years 9 months ago
A novel EDAs based method for HP model protein folding
— The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms...
Benhui Chen, Long Li, Jinglu Hu
JCM
2007
131views more  JCM 2007»
15 years 4 months ago
Routing in Optical and Non-Optical Networks using Boolean Satisfiability
—Today, most routing problems are solved using Dijkstra’s shortest path algorithm. Many efficient implementations of Dijkstra’s algorithm exist and can handle large networks ...
Fadi A. Aloul, Bashar Al Rawi, Mokhtar Aboelaze
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 10 months ago
Reducing the space-time complexity of the CMA-ES
A limited memory version of the covariance matrix adaptation evolution strategy (CMA-ES) is presented. This algorithm, L-CMA-ES, improves the space and time complexity of the CMA-...
James N. Knight, Monte Lunacek