64 search results - page 1 / 13 » Reducing the complexity of multiagent reinforcement learning |
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Transfer learning problems are typically framed as leveraging knowledge learned on a source task to improve learning on a related, but different, target task. Current transfer met...
LAMAS
2005
Springer
14 years 15 days 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
2008
Springer
13 years 9 months ago
2008
Springer
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
IAT
2008
IEEE
13 years 7 months ago
2008
IEEE
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...