The success of evolutionary methods on standard control learning tasks has created a need for new benchmarks. The classic pole balancing problem is no longer difficult enough to serve as a viable yardstick for measuring the learning efficiency of these systems. In this paper we present a more difficult version to the classic problem where the cart and pole can move in a plane. We demonstrate a neuroevolution system (Enforced Sub-Populations, or ESP) that can solve this difficult problem without velocity information.

PDF, PS

In Proceedings of the International Conference on Artificial Neural Networks (ICANN-98, Sk?Ã?¶vde, Sweden), 425-430. Berlin, New York: Springer, 1998