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IAT
2008
IEEE
15 years 10 months ago
Formalizing Multi-state Learning Dynamics
This paper extends the link between evolutionary game theory and multi-agent reinforcement learning to multistate games. In previous work, we introduced piecewise replicator dynam...
Daniel Hennes, Karl Tuyls, Matthias Rauterberg
AAMAS
2007
Springer
15 years 10 months ago
Auctions, Evolution, and Multi-agent Learning
For a number of years we have been working towards the goal of automatically creating auction mechanisms, using a range of techniques from evolutionary and multi-agent learning. Th...
Steve Phelps, Kai Cai, Peter McBurney, Jinzhong Ni...
NIPS
2001
15 years 5 months ago
Playing is believing: The role of beliefs in multi-agent learning
We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this c...
Yu-Han Chang, Leslie Pack Kaelbling
ICML
1998
IEEE
16 years 4 months ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman
AAMAS
2007
Springer
15 years 4 months ago
Generalized multiagent learning with performance bound
Abstract – Despite increasing deployment of agent technologies in several business and industry domains, user confidence in fully automated agent driven applications is noticeab...
Bikramjit Banerjee, Jing Peng