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» Learning to Coordinate Behaviors
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IROS
2007
IEEE
132views Robotics» more  IROS 2007»
14 years 1 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...
EUSFLAT
2003
165views Fuzzy Logic» more  EUSFLAT 2003»
13 years 8 months ago
Genetic fuzzy systems to evolve coordination strategies in competitive distributed systems
This paper suggests an evolutionary approach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of f...
Igor Walter, Fernando A. C. Gomide
ATAL
2008
Springer
13 years 9 months ago
Teaching multi-robot coordination using demonstration of communication and state sharing
Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teach...
Sonia Chernova, Manuela M. Veloso
IJCNN
2006
IEEE
14 years 1 months ago
Learning a Rendezvous Task with Dynamic Joint Action Perception
Abstract— Groups of reinforcement learning agents interacting in a common environment often fail to learn optimal behaviors. Poor performance is particularly common in environmen...
Nancy Fulda, Dan Ventura
JMLR
2006
153views more  JMLR 2006»
13 years 7 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis