Efficient learning equilibrium

DOI10.1016/j.artint.2004.04.013zbMath1086.68110OpenAlexW2012347046MaRDI QIDQ814627

Moshe Tennenholtz, Ronen I. Brafman

Publication date: 7 February 2006

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2004.04.013

zbMATH Keywords

EfficiencyStochastic gamesEx-post equilibriumRepeated gamesLearning equilibriumMulti-agent learning

Mathematics Subject Classification ID

Noncooperative games (91A10) Learning and adaptive systems in artificial intelligence (68T05) Stochastic games, stochastic differential games (91A15) Rationality and learning in game theory (91A26) Multistage and repeated games (91A20)

Related Items (7)

AWESOME: a general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents ⋮ A general criterion and an algorithmic framework for learning in multi-agent systems ⋮ Learning payoff functions in infinite games ⋮ If multi-agent learning is the answer, what is the question? ⋮ Perspectives on multiagent learning ⋮ Agendas for multi-agent learning ⋮ Learning equilibrium as a generalization of learning to optimize

Uses Software

• R-MAX

Cites Work

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• Subjectivity and correlation in randomized strategies
• Distributed games
• A near-optimal polynomial time algorithm for learning in certain classes of stochastic games
• Adaptive game playing using multiplicative weights
• Bundling equilibrium in combinatorial auctions
• 10.1162/153244303765208377
• An Approach to Communication Equilibria
• The Folk Theorem in Repeated Games with Discounting or with Incomplete Information
• Equilibrium points in n -person games
• Stochastic Games

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