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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 6 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
SIGGRAPH
1998
ACM
15 years 6 months ago
Reproducing Color Images Using Custom Inks
We investigate the general problem of reproducing color images on an offset press using custom inks in any combination and number. While this problem has been explored previously ...
Eric J. Stollnitz, Victor Ostromoukhov, David Sale...
CEC
2008
IEEE
15 years 8 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
110
Voted
BMCBI
2007
168views more  BMCBI 2007»
15 years 2 months ago
Benchmarking consensus model quality assessment for protein fold recognition
Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. M...
Liam J. McGuffin
115
Voted
TEC
2002
161views more  TEC 2002»
15 years 1 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...