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» Using evolution strategies to solve DEC-POMDP problems
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CEC
2005
IEEE
15 years 7 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»
15 years 3 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»
15 years 5 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
15 years 3 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»
15 years 11 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