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» Error Bounds for Approximate Policy Iteration
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ML
2008
ACM
152views Machine Learning» more  ML 2008»
13 years 4 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...

Publication
222views
14 years 1 months ago
Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Christos Dimitrakakis, Michail G. Lagoudakis
NIPS
2003
13 years 5 months ago
Bounded Finite State Controllers
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...
Pascal Poupart, Craig Boutilier
ICIP
1999
IEEE
14 years 6 months ago
Efficient Approximation of Gray-Scale Images Through Bounded Error Triangular Meshes
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...