Adaptive Multi−Agent Programming in GTGolog

Conference item

We present a novel approach to adaptive multi-agent programming, which is based on an integration of the agent programming language GTGolog with adaptive dynamic programming techniques. GTGolog combines explicit agent programming in Golog with game-theoretic multi-agent planning in stochastic games. In GTGolog, the transition probabilities and reward values of the domain must be provided with the model. The adaptive generalization of GTGolog proposed here is directed towards letting the agents themselves explore and adapt these data. We use high-level programs for the generation of both abstract states and optimal policies.

Authors: Finzi, A; Lukasiewicz, T

• Publisher: IOS Press
• Host title: Proceedings of the 17th European Conference on Artificial Intelligence‚ ECAI 2006‚ Riva del Garda‚ Italy‚ August 29 − September 1‚ 2006
• Volume: 141
• Publication date: 2006-01-01
• ISBN: 1586036424