20 search results - page 1 / 4 » Multiagent learning in large anonymous games |
131
Voted
ATAL
2009
Springer
15 years 10 months ago
2009
Springer
In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to ï...
130
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NIPS
2003
15 years 5 months ago
2003
In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efï¬...
142
Voted
AIIDE
2006
15 years 5 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
152
Voted
ATAL
2011
Springer
14 years 3 months ago
2011
Springer
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
112
Voted
ICML
2003
IEEE
16 years 4 months ago
2003
IEEE
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...