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» Q-Decomposition for Reinforcement Learning Agents
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ESANN
2008
13 years 9 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
ATAL
2007
Springer
14 years 1 months ago
Advice taking in multiagent reinforcement learning
This paper proposes the β-WoLF algorithm for multiagent reinforcement learning (MARL) in the stochastic games framework that uses an additional “advice” signal to inform agen...
Michael Rovatsos, Alexandros Belesiotis
AAAI
1997
13 years 9 months ago
Reinforcement Learning with Time
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
Daishi Harada
ATAL
2007
Springer
14 years 1 months ago
Reinforcement learning in extensive form games with incomplete information: the bargaining case study
We consider the problem of finding optimal strategies in infinite extensive form games with incomplete information that are repeatedly played. This problem is still open in lite...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Ni...
FLAIRS
2007
13 years 10 months ago
A Generalizing Spatial Representation for Robot Navigation with Reinforcement Learning
In robot navigation tasks, the representation of the surrounding world plays an important role, especially in reinforcement learning approaches. This work presents a qualitative r...
Lutz Frommberger