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» Particle Swarm Optimization Using Adaptive Mutation
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CEC
2007
IEEE
15 years 3 months ago
Parallel learning in heterogeneous multi-robot swarms
Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
Jim Pugh, Alcherio Martinoli
PPSN
2004
Springer
15 years 2 months ago
LS-CMA-ES: A Second-Order Algorithm for Covariance Matrix Adaptation
Abstract. Evolution Strategies, Evolutionary Algorithms based on Gaussian mutation and deterministic selection, are today considered the best choice as far as parameter optimizatio...
Anne Auger, Marc Schoenauer, Nicolas Vanhaecke
GECCO
2007
Springer
196views Optimization» more  GECCO 2007»
15 years 3 months ago
An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem
An Estimation of Distribution Algorithm (EDA) is proposed to approach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFSSDST-UM) proble...
Abdellah Salhi, José Antonio Vázquez...
NCA
2007
IEEE
14 years 9 months ago
Ensemble of hybrid neural network learning approaches for designing pharmaceutical drugs
Designing drugs is a current problem in the pharmaceutical research. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal charac...
Ajith Abraham, Crina Grosan, Stefan Tigan
AE
2005
Springer
15 years 3 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud