56 search results - page 9 / 12 » Multi-Agent Inverse Reinforcement Learning |
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
PPSN
2004
Springer
14 years 24 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 28 days 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...