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» Compositional Models for Reinforcement Learning
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ICML
2003
IEEE
14 years 29 days ago
The Influence of Reward on the Speed of Reinforcement Learning: An Analysis of Shaping
Shaping can be an effective method for improving the learning rate in reinforcement systems. Previously, shaping has been heuristically motivated and implemented. We provide a for...
Adam Laud, Gerald DeJong
ATAL
2010
Springer
13 years 8 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
CORR
2006
Springer
101views Education» more  CORR 2006»
13 years 7 months ago
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...
ICML
2002
IEEE
14 years 8 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ECML
2004
Springer
14 years 1 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls