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ATAL
2009
Springer
14 years 2 months ago
Multiagent learning in large anonymous games
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 ...
Ian A. Kash, Eric J. Friedman, Joseph Y. Halpern
ATAL
2010
Springer
13 years 8 months ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings
SIGECOM
2006
ACM
139views ECommerce» more  SIGECOM 2006»
14 years 1 months ago
Playing games in many possible worlds
In traditional game theory, players are typically endowed with exogenously given knowledge of the structure of the game—either full omniscient knowledge or partial but fixed in...
Matt Lepinski, David Liben-Nowell, Seth Gilbert, A...
SAGT
2010
Springer
127views Game Theory» more  SAGT 2010»
13 years 6 months ago
On the Rate of Convergence of Fictitious Play
Fictitious play is a simple learning algorithm for strategic games that proceeds in rounds. In each round, the players play a best response to a mixed strategy that is given by the...
Felix Brandt, Felix A. Fischer, Paul Harrenstein