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ICCCI
2011
Springer
14 years 4 months ago
Evolving Equilibrium Policies for a Multiagent Reinforcement Learning Problem with State Attractors
Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...
Florin Leon
EUROGP
2005
Springer
115views Optimization» more  EUROGP 2005»
15 years 10 months ago
Genetic Programming in Wireless Sensor Networks
Abstract. Wireless sensor networks (WSNs) are medium scale manifestations of a paintable or amorphous computing paradigm. WSNs are becoming increasingly important as they attain gr...
Derek M. Johnson, Ankur Teredesai, Robert T. Salta...
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 10 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
BIOINFORMATICS
2006
106views more  BIOINFORMATICS 2006»
15 years 5 months ago
Identification of biochemical networks by S-tree based genetic programming
Motivation: Most previous approaches to model biochemical networks havefocusedeither on the characterization of a networkstructurewith a number of components or on the estimation ...
Dong-Yeon Cho, Kwang-Hyun Cho, Byoung-Tak Zhang
163
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EVOW
2005
Springer
15 years 10 months ago
On the Application of Evolutionary Algorithms to the Consensus Tree Problem
Computing consensus trees amounts to finding a single tree that summarizes a collection of trees. Three evolutionary algorithms are defined for this problem, featuring characteri...
Carlos Cotta