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IAT
2008
IEEE
13 years 5 months ago
Scaling Up Multi-agent Reinforcement Learning in Complex Domains
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
Dan Xiao, Ah-Hwee Tan
ECML
2004
Springer
13 years 10 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
13 years 12 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
KES
2004
Springer
13 years 10 months ago
Coordination in Multiagent Reinforcement Learning Systems
This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action ...
M. A. S. Kamal, Junichi Murata
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
13 years 11 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu