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AAMAS
2002
Springer
14 years 9 months ago
Multiagent Learning for Open Systems: A Study in Opponent Classification
Abstract. Open systems are becoming increasingly important in a variety of distributed, networked computer applications. Their characteristics, such as agent diversity, heterogenei...
Michael Rovatsos, Gerhard Weiß, Marco Wolf
NIPS
2003
14 years 11 months ago
All learning is Local: Multi-agent Learning in Global Reward Games
In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efï¬...
Yu-Han Chang, Tracey Ho, Leslie Pack Kaelbling
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
15 years 4 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
ICML
2003
IEEE
15 years 10 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm
AAAI
1997
14 years 11 months ago
Planning with Concurrent Interacting Actions
In order to generate plans for agents with multiple actuators or agent teams, we must be able to represent and plan using concurrent actions with interacting effects. Historically...
Craig Boutilier, Ronen I. Brafman