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» Using Reinforcement Learning to Coordinate Better
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LAMAS
2005
Springer
13 years 10 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
AAAI
1994
13 years 6 months ago
Learning to Coordinate without Sharing Information
Researchers in the eld of Distributed Arti cial Intelligence (DAI) have been developing e cient mechanisms to coordinate the activities of multiple autonomous agents. The need for...
Sandip Sen, Mahendra Sekaran, John Hale
WOSS
2004
ACM
13 years 10 months ago
Self-managed decentralised systems using K-components and collaborative reinforcement learning
Components in a decentralised system are faced with uncertainty as how to best adapt to a changing environment to maintain or optimise system performance. How can individual compo...
Jim Dowling, Vinny Cahill
ECML
2005
Springer
13 years 11 months ago
Towards Finite-Sample Convergence of Direct Reinforcement Learning
Abstract. While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees f...
Shiau Hong Lim, Gerald DeJong
ICMLA
2008
13 years 6 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux