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» On the Approximation of Computing Evolutionary Trees
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IPPS
2007
IEEE
15 years 4 months ago
Parallel Processing for Multi-objective Optimization in Dynamic Environments
This paper deals with the use of parallel processing for multi-objective optimization in applications in which the objective functions, the restrictions, and hence also the soluti...
Mario Cámara, Julio Ortega, Francisco de To...
EMO
2005
Springer
194views Optimization» more  EMO 2005»
15 years 3 months ago
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
Abstract. The hypervolume measure is one of the most frequently applied measures for comparing the results of evolutionary multiobjective optimization algorithms (EMOA). The idea t...
Michael Emmerich, Nicola Beume, Boris Naujoks
CEC
2011
IEEE
13 years 9 months ago
Trainer selection strategies for coevolving rank predictors
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
Daniel L. Ly, Hod Lipson
AAAI
2012
13 years 4 days ago
Generalized Sampling and Variance in Counterfactual Regret Minimization
In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. Whi...
Richard G. Gibson, Marc Lanctot, Neil Burch, Duane...
PPSN
2004
Springer
15 years 3 months ago
Experimental Supplements to the Theoretical Analysis of EAs on Problems from Combinatorial Optimization
It is typical for the EA community that theory follows experiments. Most theoretical approaches use some model of the considered evolutionary algorithm (EA) but there is also some ...
Patrick Briest, Dimo Brockhoff, Bastian Degener, M...