170 search results - page 18 / 34 » Heuristic Selection of Actions in Multiagent Reinforcement L... |
EUROCAST
2007
Springer
14 years 1 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
IAT
2010
IEEE
13 years 5 months ago
2010
IEEE
It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In t...
ATAL
2007
Springer
13 years 11 months ago
2007
Springer
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...
ATAL
2006
Springer
13 years 11 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...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...