Reinforcement learning in steady-state cellular genetic algorithms

A novel cellular genetic algorithm is developed to address the issues of good mate selection. This is accomplished through reinforcement learning where good mating individuals attract and poor mating individuals repel. Adaptation of good mate choice occurs, thus leading to more efficient search. Results are presented for various test cases.