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» Policy Gradient Method for Team Markov Games
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IDEAL
2004
Springer
13 years 10 months ago
Policy Gradient Method for Team Markov Games
The main aim of this paper is to extend the single-agent policy gradient method for multiagent domains where all agents share the same utility function. We formulate these team pro...
Ville Könönen
JMLR
2010
189views more  JMLR 2010»
12 years 11 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...
NIPS
2003
13 years 6 months ago
Distributed Optimization in Adaptive Networks
We develop a protocol for optimizing dynamic behavior of a network of simple electronic components, such as a sensor network, an ad hoc network of mobile devices, or a network of ...
Ciamac Cyrus Moallemi, Benjamin Van Roy
ATAL
2008
Springer
13 years 6 months ago
Emerging coordination in infinite team Markov games
In this paper we address the problem of coordination in multi-agent sequential decision problems with infinite statespaces. We adopt a game theoretic formalism to describe the int...
Francisco S. Melo, M. Isabel Ribeiro
JMLR
2006
143views more  JMLR 2006»
13 years 4 months ago
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
Rémi Munos