2-D Pole Balancing With Recurrent Evolutionary Networks (1998)
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.
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Citation:
In Proceedings of the International Conference on Artificial Neural Networks (ICANN-98), pp. 425-430, Skovde, Sweden 1998. Berlin, New York: Springer.
Bibtex:

Faustino Gomez Postdoctoral Alumni tino [at] idsia ch
Faustino Gomez Postdoctoral Alumni tino [at] idsia ch
Risto Miikkulainen Faculty risto [at] cs utexas edu
ESP C++ The ESP package contains the source code for the Enforced Sup-Populations system written in C++. ESP is an extension t... 2000