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IROS
2008
IEEE
125views Robotics» more  IROS 2008»
14 years 2 months ago
Dynamic correlation matrix based multi-Q learning for a multi-robot system
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Hongliang Guo, Yan Meng
ATAL
2007
Springer
14 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
IJAR
2008
118views more  IJAR 2008»
13 years 7 months ago
Dynamic multiagent probabilistic inference
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Xiangdong An, Yang Xiang, Nick Cercone
AGENTS
1999
Springer
13 years 12 months ago
On Being a Teammate: Experiences Acquired in the design of RoboCup Teams
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. E ective agent interactions in such domains raise some of most fundamental research...
Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Gal...
ROBOCUP
2005
Springer
140views Robotics» more  ROBOCUP 2005»
14 years 1 months ago
Cooperative Action Control Based on Evaluating Objective Achievements
This paper deals with a cooperative control method for a multi-agent system in dynamic environment. This method enables a robot to perform flexible cooperation based on the global ...
Hikari Fujii, Masayuki Kato, Kazuo Yoshida