332 search results - page 25 / 67 » Ranking policies in discrete Markov decision processes |
ALDT
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
ATAL
2007
Springer
14 years 2 months ago
2007
Springer
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...