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GECCO
2004
Springer

An Estimation of Distribution Algorithm Based on Maximum Entropy

11 years 7 months ago
An Estimation of Distribution Algorithm Based on Maximum Entropy
Estimation of distribution algorithms (EDA) are similar to genetic algorithms except that they replace crossover and mutation with sampling from an estimated probability distribution. We develop a framework for estimation of distribution algorithms based on the principle of maximum entropy and the conservation of schema frequencies. An algorithm of this type gives better performance than a standard genetic algorithm (GA) on a number of standard test problems involving deception and epistasis (i.e. Trap and NK).
Alden H. Wright, Riccardo Poli, Christopher R. Ste
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where GECCO
Authors Alden H. Wright, Riccardo Poli, Christopher R. Stephens, William B. Langdon, Sandeep Pulavarty
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