64 search results - page 2 / 13 » Reducing the complexity of multiagent reinforcement learning |
ATAL
2005
Springer
13 years 10 months ago
2005
Springer
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
AI
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. Choosing between multiple alternative tasks is a hard problem for agents evolving in an uncertain real-time multiagent environment. An example of such environment is the ...
ROBOCUP
2007
Springer
13 years 11 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
TSMC
2008
13 years 4 months ago
2008
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
ATAL
2010
Springer
13 years 6 months ago
2010
Springer
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...