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ICML
1996
IEEE
15 years 1 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
COR
2008
142views more  COR 2008»
14 years 9 months ago
Application of reinforcement learning to the game of Othello
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
Nees Jan van Eck, Michiel C. van Wezel
ICDE
2007
IEEE
140views Database» more  ICDE 2007»
15 years 11 months ago
Selecting Stars: The k Most Representative Skyline Operator
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of selecting k skyline points so that the number of points,...
Xuemin Lin, Yidong Yuan, Qing Zhang, Ying Zhang
ATAL
2008
Springer
14 years 11 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
AAAI
2012
13 years 2 days ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous