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AAAI
1998
13 years 9 months ago
The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
Caroline Claus, Craig Boutilier
ALT
2010
Springer
13 years 10 months ago
A Regularization Approach to Metrical Task Systems
We address the problem of constructing randomized online algorithms for the Metrical Task Systems (MTS) problem on a metric against an oblivious adversary. Restricting our attenti...
Jacob Abernethy, Peter L. Bartlett, Niv Buchbinder...
ICML
2001
IEEE
14 years 9 months ago
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
Martin Zinkevich, Tucker R. Balch
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
KES
2004
Springer
14 years 1 months ago
Coordination in Multiagent Reinforcement Learning Systems
This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action ...
M. A. S. Kamal, Junichi Murata