Approximate strategic reasoning through hierarchical reduction of large symmetric games

Author

Michael P. WELLMAN, University of Michigan
Daniel M. REEVES
Kevin M. LOCHNER
Shih-Fen CHENG, Singapore Management UniversityFollow
Rahul SURI

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2005

Abstract

To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated local-effect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity.

Discipline

Artificial Intelligence and Robotics | Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering

Publication

Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05): July 9-13, 2005, Pittsburgh, PA

First Page

502

Last Page

508

ISBN

9781577352365

Publisher

AAAI Press

City or Country

Menlo Park, CA

Citation

WELLMAN, Michael P.; REEVES, Daniel M.; LOCHNER, Kevin M.; CHENG, Shih-Fen; and SURI, Rahul. Approximate strategic reasoning through hierarchical reduction of large symmetric games. (2005). Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05): July 9-13, 2005, Pittsburgh, PA. 502-508.
Available at: https://ink.library.smu.edu.sg/sis_research/1200

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.6230