374 search results - page 38 / 75 » Multiagent Reinforcement Learning: Theoretical Framework and... |
SMC
2007
IEEE
14 years 2 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
FOCS
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— Applications in complex systems such as the Internet have spawned recent interest in studying situations involving multiple agents with their individual cost or utility...
AAAI
2008
13 years 10 months ago
2008
Hierarchical state decompositions address the curse-ofdimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, w...
ATAL
2006
Springer
13 years 9 months ago
2006
Springer
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
NIPS
2007
13 years 9 months ago
2007
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...