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» Feudal Reinforcement Learning
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FLAIRS
2003
13 years 9 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
ICML
2010
IEEE
13 years 9 months ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...
HIS
2004
13 years 9 months ago
Stigmergy in Multi Agent Reinforcement Learning
In this paper, we describe how certain aspects of the biological phenomena of stigmergy can be imported into multiagent reinforcement learning (MARL), with the purpose of better e...
Raghav Aras, Alain Dutech, François Charpil...
ACMACE
2007
ACM
14 years 4 days ago
Motivated reinforcement learning for adaptive characters in open-ended simulation games
Recently a new generation of virtual worlds has emerged in which users are provided with open-ended modelling tools with which they can create and modify world content. The result...
Kathryn Elizabeth Merrick, Mary Lou Maher
KDD
2010
ACM
282views Data Mining» more  KDD 2010»
14 years 1 days ago
Optimizing debt collections using constrained reinforcement learning
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....