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» Multiagent Reinforcement Learning: Theoretical Framework and...
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ATAL
2004
Springer
14 years 1 months ago
From Global Selective Perception to Local Selective Perception
This paper presents a reinforcement learning algorithm used to allocate tasks to agents in an uncertain real-time environment. In such environment, tasks have to be analyzed and a...
Sébastien Paquet, Nicolas Bernier, Brahim C...
ATAL
2004
Springer
14 years 1 months ago
Adaptive, Distributed Control of Constrained Multi-Agent Systems
Product Distribution (PD) theory was recently developed as a framework for analyzing and optimizing distributed systems. In this paper we demonstrate its use for adaptive distribu...
Stefan Bieniawski, David Wolpert
ICML
1999
IEEE
14 years 8 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
14 years 2 months ago
Learning Complementary Multiagent Behaviors: A Case Study
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Shivaram Kalyanakrishnan, Peter Stone
ATAL
2003
Springer
14 years 27 days ago
Coordination in multiagent reinforcement learning: a Bayesian approach
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...
Georgios Chalkiadakis, Craig Boutilier