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» Approximating Markov Processes by Averaging
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115
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AAAI
1998
15 years 3 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
ICML
2006
IEEE
16 years 2 months ago
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes
Policy evaluation is a critical step in the approximate solution of large Markov decision processes (MDPs), typically requiring O(|S|3 ) to directly solve the Bellman system of |S...
Mauro Maggioni, Sridhar Mahadevan
124
Voted
ECAI
2000
Springer
15 years 5 months ago
Efficient Asymptotic Approximation in Temporal Difference Learning
Abstract. TD(
Frédérick Garcia, Florent Serre
106
Voted
CORR
2010
Springer
112views Education» more  CORR 2010»
15 years 1 months ago
Efficient Approximation of Optimal Control for Markov Games
The success of probabilistic model checking for discrete-time Markov decision processes and continuous-time Markov chains has led to rich academic and industrial applications. The ...
Markus Rabe, Sven Schewe, Lijun Zhang
150
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JMLR
2010
189views more  JMLR 2010»
14 years 8 months ago
Adaptive Step-size Policy Gradients with Average Reward Metric
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
Takamitsu Matsubara, Tetsuro Morimura, Jun Morimot...