Learning for stochastic dynamic programming
Sylvain Gelly, Jeremie Mary and Olivier Teytaud
In: 11th European Symposium on Artificial Neural Networks, 26 - 28 April, Bruges Belgium.
We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourceforge.net), a freely available source code, and therefore can be reproduced. The goal is an independent comparison of learning methods in the framework of SDP.