Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
We show how a random mutation hill climber that does multilevel selection utilizes transposition to escape local optima on the discrete Hierarchical-If-And-Only-If (HIFF) problem....
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Ant Colony Optimization (ACO) has been successfully applied to those combinatorial optimization problems which can be translated into a graph exploration. Artificial ants build s...
During recent years there has been an explosive growth of biological data coming from genome projects, proteomics, protein structure determination, and the rapid expansion in digi...
Nasreddine Hireche, J. M. Pierre Langlois, Gabriel...