Evolving controllers for simulated car racing using object oriented genetic programming

Alexandros Agapitos, Julian Togelius, Simon M. Lucas

Abstract: Several different controller representations are compared on anon-trivial problem in simulated car racing, with respect tolearning speed and final fitness. The controller representations arebased either on Neural Networks or Genetic Programming, and alsodiffer in regards to whether they allow for stateful controllers orjust reactive ones. Evolved GP trees are analysed, and attempts aremade at explaining the performance differences observed.