Abstract
In this paper, extended experience-repository-based Particle Swarm Optimization (EERPSO) is proposed for effectively applying Particle Swarm Optimization (PSO) to evolutionary robotics applications. It is an extension of our previous algorithm, called experience-repository-based Particle Swarm Optimization (ERPSO) which has the fast convergence property. The ERPSO uses a concept an experience repository to store previous position and fitness of particles of the PSO algorithms to accelerate the convergence speed. EERPSO additionally has an experience repository manager that selects particles to be included in the experience repository, and improved estimated best position selection mechanism in the ERPSO that balance exploitation and exploration of the EERPSO. We applied the EERPSO to find parameters of a gait of a quadruped robot for producing a fast gait. The EERPSO showed best performance among the original PSO, PSO and PSO variants, and ERPSO.
