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IJCAI
2001
13 years 5 months ago
Reinforcement Learning in Distributed Domains: Beyond Team Games
Using a distributed algorithm rather than a centralized one can be extremely beneficial in large search problems. In addition, the incorporation of machine learning techniques lik...
David Wolpert, Joseph Sill, Kagan Tumer
IROS
2007
IEEE
132views Robotics» more  IROS 2007»
13 years 10 months ago
Hysteretic q-learning : an algorithm for decentralized reinforcement learning in cooperative multi-agent teams
— Multi-agent systems (MAS) are a field of study of growing interest in a variety of domains such as robotics or distributed controls. The article focuses on decentralized reinf...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
AAAI
2012
11 years 6 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...
ICARCV
2006
IEEE
100views Robotics» more  ICARCV 2006»
13 years 9 months ago
Decentralized Reinforcement Learning Control of a Robotic Manipulator
— Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Learning approaches to multi-ag...
Lucian Busoniu, Bart De Schutter, Robert Babuska

Publication
233views
12 years 2 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis