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GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 1 months ago
Screening the parameters affecting heuristic performance
This research screens the tuning parameters of a combinatorial optimization heuristic. Specifically, it presents a Design of Experiments (DOE) approach that uses a Fractional Fac...
Enda Ridge, Daniel Kudenko
ATAL
2003
Springer
14 years 23 days ago
Integrating evolutionary computing and the SADDE methodology
This paper introduces a methodology to help the programmer in the transition from a set of desired global properties expressed as an equation-based model (EBM) that a Multi-Agent ...
Carles Sierra, Jordi Sabater, Jaume Agustí-...
GECCO
2008
Springer
257views Optimization» more  GECCO 2008»
13 years 8 months ago
Rapid evaluation and evolution of neural models using graphics card hardware
This paper compares three common evolutionary algorithms and our modified GA, a Distributed Adaptive Genetic Algorithm (DAGA). The optimal approach is sought to adapt, in near rea...
Thomas F. Clayton, Leena N. Patel, Gareth Leng, Al...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 1 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels
ICGA
2008
208views Optimization» more  ICGA 2008»
13 years 7 months ago
Cross-Entropy for Monte-Carlo Tree Search
Recently, Monte-Carlo Tree Search (MCTS) has become a popular approach for intelligent play in games. Amongst others, it is successfully used in most state-of-the-art Go programs....
Guillaume Chaslot, Mark H. M. Winands, Istvan Szit...