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ICANN
2001
Springer
14 years 2 months ago
Market-Based Reinforcement Learning in Partially Observable Worlds
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
IJCAI
2003
13 years 11 months ago
A Bayesian Approach to Imitation in Reinforcement Learning
In multiagent environments, forms of social learning such as teaching and imitation have been shown to aid the transfer of knowledge from experts to learners in reinforcement lear...
Bob Price, Craig Boutilier
ATAL
2008
Springer
13 years 12 months ago
Analysis of an evolutionary reinforcement learning method in a multiagent domain
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
IJCNN
2006
IEEE
14 years 4 months ago
Reinforcement Learning for Platform-Independent Visual Robot Control
—This paper proposes a new architecture for robot control. A test scenario is outlined to test the proposed system and enable a comparison with an existing system, which is able ...
David Muse, Kevin Burn, Stefan Wermter
ESOA
2006
14 years 1 months ago
Reinforcement Learning for Online Control of Evolutionary Algorithms
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). ...
A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Marti...