Introducing Particle Swarm Optimization into a Genetic Algorithm to Evolve Robot Controllers’
In Proceedings of the RIC Project Day Workgroups Locomotion&Simulation, 17.9.-17.9.2015, Bremen, Selbstverlag, volume 14_06, number 1406, Sep/2015. Robotics Innovation Center Bremen.
This paper presents Swarm-Assisted Behavior Graph Evolution (Sabre), a genetic algorithm which combines
elements from genetic programming and neuroevolution to develop Behavior Graphs (Bgs). Sabre evolves
graph structure and parameters in parallel using particle swarm optimization (Pso) for the latter. The
algorithm’s performance was evaluated on a set of black-box function approximation problems, one of which
represents part of a robot controller. We found that Sabre performed significantly better in approximating
the mathematically complex test functions than the reference algorithms genetic programming (Gp) and