UTCS Artificial Intelligence
CoSyNE is a neuroevolution method where synapses of the network are evolved in separate subpopulations in a cooperative fashion. It is particularly powerful in control tasks such as double pole balancing, where it has performed better than other methods. The code is structured so that it is easy to apply it to other tasks by changing the environment class.
tino [at] idsia ch
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen,
Journal of Machine Learning Research
(2008), pp. 937-965.
Efficient Non-Linear Control through Neuroevolution
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, In
Proceedings of the European Conference on Machine Learning
, pp. 654-662, Berlin 2006. Springer.
Areas of Interest