98 search results - page 9 / 20 » Hierarchical multi-agent reinforcement learning |
ATAL
2006
Springer
13 years 11 months ago
2006
Springer
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
PPSN
2004
Springer
14 years 26 days ago
2004
Springer
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
AAMAS
2007
Springer
14 years 1 months ago
2007
Springer
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
LAMAS
2005
Springer
14 years 1 months ago
2005
Springer
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
TSMC
2008
13 years 7 months ago
2008
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...