The experience described in this paper is being developed in the framework of the PALETTE1 project by two teams of researchers involved in collecting information from some Communi...
Amaury Daele, Martin Erpicum, Liliane Esnault, Fab...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Creation of the reusable learning content in the process of work is a challenging but promising trend in e-learning and knowledge management. While the main research focus nowadays...
Abstract. We provide a natural learning process in which the joint frequency of empirical play converges into the set of convex combinations of Nash equilibria. In this process, al...
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...