2 search results - page 1 / 1 » Co-evolving recurrent neurons learn deep memory POMDPs |
GECCO
2005
Springer
14 years 28 days ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
ICANN
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. This paper presents Recurrent Policy Gradients, a modelfree reinforcement learning (RL) method creating limited-memory stochastic policies for partially observable Markov...