10 search results - page 1 / 2 » Learning to cooperate in multi-agent social dilemmas |
ATAL
2006
Springer
13 years 11 months ago
2006
Springer
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
ECAI
2006
Springer
13 years 11 months ago
2006
Springer
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
This paper presents a framework for describing the spatial distribution and the global frequency of agents who play the spatial prisoner’s dilemma with coalition formation. The ...