Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
We describe a new approximation algorithm for solving partially observable MDPs. Our bounded policy iteration approach searches through the space of bounded-size, stochastic fini...
This paper presents an iterative algorithm for approximating gray-scale images with adaptive triangular meshes ensuring a given tolerance. At each iteration, the algorithm applies...
Angel Domingo Sappa, Boris Xavier Vintimilla, Migu...