374 search results - page 6 / 75 » Multiagent Reinforcement Learning: Theoretical Framework and... |
CEEMAS
2003
Springer
14 years 26 days ago
2003
Springer
Modeling learning agents in the context of Multi-agent Systems requires an adequate understanding of their dynamic behaviour. Usually, these agents are modeled similar to the di...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
Mediation is the process of decomposing a task into subtasks, finding agents suitable for these subtasks and negotiating with agents to obtain commitments to execute these subtas...
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...