64 search results - page 4 / 13 » Reducing the complexity of multiagent reinforcement learning |
AAMAS
2007
Springer
13 years 7 months ago
2007
Springer
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
This paper proposes the β-WoLF algorithm for multiagent reinforcement learning (MARL) in the stochastic games framework that uses an additional “advice” signal to inform agen...
AGENTS
1999
Springer
13 years 11 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
JAIR
2008
13 years 7 months ago
2008
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Due to the complexity of the problem, the majority of the previo...