145 search results - page 4 / 29 » Coordinating Multiple Agents via Reinforcement Learning |
ATAL
2009
Springer
14 years 25 days ago
2009
Springer
Creating coordinated multiagent policies in environments with uncertainty is a challenging problem, which can be greatly simplified if the coordination needs are known to be limi...
KCAP
2009
ACM
14 years 23 days ago
2009
ACM
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
ATAL
2006
Springer
13 years 10 months ago
2006
Springer
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
LAMAS
2005
Springer
13 years 11 months ago
2005
Springer
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
ATAL
2010
Springer
13 years 7 months ago
2010
Springer
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...