Approximate Strategic Reasoning Through Hierarchical Reduction of Large Symmetric Games
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 sav-ings 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 ap-plication to strategic reasoning about a complex trading sce-nario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity.
Cite
Text
Wellman et al. "Approximate Strategic Reasoning Through Hierarchical Reduction of Large Symmetric Games." AAAI Conference on Artificial Intelligence, 2005.Markdown
[Wellman et al. "Approximate Strategic Reasoning Through Hierarchical Reduction of Large Symmetric Games." AAAI Conference on Artificial Intelligence, 2005.](https://mlanthology.org/aaai/2005/wellman2005aaai-approximate/)BibTeX
@inproceedings{wellman2005aaai-approximate,
title = {{Approximate Strategic Reasoning Through Hierarchical Reduction of Large Symmetric Games}},
author = {Wellman, Michael P. and Reeves, Daniel M. and Lochner, Kevin M. and Cheng, Shih-Fen and Suri, Rahul},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2005},
pages = {502-508},
url = {https://mlanthology.org/aaai/2005/wellman2005aaai-approximate/}
}