Abstract

In this paper we study a class of resource allocation games which are inspired by the El Farol Bar problem. We consider a system of competitive agents that have to choose between several resources characterized by their time dependent capacities. The agents using a particular resource are rewarded if their number does not exceed the resource capacity, and punished otherwise. Agents use a set of strategies to decide what resource to choose, and use a simple reinforcement learning scheme to update the accuracy of strategies. A strategy in our model is simply a lookup table that suggests to an agent what resource to choose based on the actions of its neighbors at the previous time step. In other words, the agents form a social network whose connectivity controls the average number of neighbors with whom each agent interacts. This statement of the adaptive resource allocation problem allows us to fully …

Date

July 14, 2003

Authors

Aram Galstyan, Shashikiran Kolar, Kristina Lerman

Book

Proceedings of the second international joint conference on Autonomous agents and multiagent systems

Pages

145-152