64 search results - page 1 / 13 » Reducing the complexity of multiagent reinforcement learning |
ATAL
2007
Springer
13 years 10 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
13 years 10 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
13 years 10 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
2008
Springer
13 years 6 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 4 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 (...