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» Using evolution strategies to solve DEC-POMDP problems
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CEC
2005
IEEE
13 years 10 months ago
Evolution and prioritization of survival strategies for a simulated robot in Xpilot
Simulated evolution by the use of Genetic Algorithms (GA) is presented as the solution to a twofaceted problem: the challenge for an autonomous agent to learn the reactive componen...
Gary B. Parker, Timothy S. Doherty, Matt Parker
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
TEC
2002
120views more  TEC 2002»
13 years 7 months ago
Optimization based on bacterial chemotaxis
We present an optimization algorithm based on a model of bacterial chemotaxis. The original biological model is used to formulate a simple optimization algorithm, which is evaluate...
Sibylle D. Müller, Jarno Marchetto, Stefano A...
CLOUDCOM
2010
Springer
13 years 6 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin
GECCO
2004
Springer
120views Optimization» more  GECCO 2004»
14 years 1 months ago
Comparison of Selection Strategies for Evolutionary Quantum Circuit Design
Evolution of quantum circuits faces two major challenges: complex and huge search spaces and the high costs of simulating quantum circuits on conventional computers. In this paper ...
André Leier, Wolfgang Banzhaf