Relational Markov Games
Alberto Finzi and Thomas Lukasiewicz
Abstract
Towards a compact and elaboration-tolerant first-order representation of Markov games, we introduce relational Markov games, which combine standard Markov games with first-order action descriptions in a stochastic variant of the situation calculus. We focus on the zero-sum two-agent case, where we have two agents with diametrically opposed goals. We also present a symbolic value iteration algorithm for computing Nash policy pairs in this framework.
Book Title
Proceedings of the 9th European Conference on Logics in Artificial Intelligence‚ JELIA 2004‚ Lisbon‚ Portugal‚ September 27−30‚ 2004
Editor
José Júlio Alferes and João Alexandre Leite
ISBN
3−540−23242−7
Pages
320−333
Publisher
Springer
Series
Lecture Notes in Computer Science
Volume
3229
Year
2004