On complexity as bounded rationality (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Efficient algorithms for learning to play repeated games against computationally bounded adversaries
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
An overview of cooperative and competitive multiagent learning
LAMAS'05 Proceedings of the First international conference on Learning and Adaption in Multi-Agent Systems
Unifying convergence and no-regret in multiagent learning
LAMAS'05 Proceedings of the First international conference on Learning and Adaption in Multi-Agent Systems
A brief introduction to agent mining
Autonomous Agents and Multi-Agent Systems
A common gradient in multi-agent reinforcement learning
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
General-sum stochastic games: Verifiability conditions for Nash equilibria
Automatica (Journal of IFAC)
Multi-agent learning and the reinforcement gradient
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Expert Systems with Applications: An International Journal
Multiagent learning in the presence of memory-bounded agents
Autonomous Agents and Multi-Agent Systems
Multiagent meta-level control for radar coordination
Web Intelligence and Agent Systems
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Multi-agent games are becoming an increasingly prevalent formalism for the study of electronic commerce and auctions. The speed at which transactions can take place and the growing complexity of electronic marketplaces makes the study of computationally simple agents an appealing direction. In this work, we analyze the behavior of agents that incrementally adapt their strategy through gradient ascent on expected payoff, in the simple setting of two-player, two-action, iterated general-sum games, and present a surprising result. We show that either the agents will converge to a Nash equilibrium, or if the strategies themselves do not converge, then their average payoffs will nevertheless converge to the payoffs of a Nash equilibrium.