Beyond Equilibrium: Predicting Human Behavior in Normal-Form Games
Abstract
It is standard in multiagent settings to assume that agents will adopt Nash equilibrium strategies. However, studies in experimental economics demonstrate that Nash equilibrium is a poor description of human players' initial behavior in normal-form games. In this paper, we consider a wide range of widely-studied models from behavioral game theory. For what we believe is the first time, we evaluate each of these models in a meta-analysis, taking as our data set large-scale and publicly-available experimental data from the literature. We then propose modifications to the best-performing model that we believe make it more suitable for practical prediction of initial play by humans in normal-form games.
Cite
Text
Wright and Leyton-Brown. "Beyond Equilibrium: Predicting Human Behavior in Normal-Form Games." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7644Markdown
[Wright and Leyton-Brown. "Beyond Equilibrium: Predicting Human Behavior in Normal-Form Games." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/wright2010aaai-beyond/) doi:10.1609/AAAI.V24I1.7644BibTeX
@inproceedings{wright2010aaai-beyond,
title = {{Beyond Equilibrium: Predicting Human Behavior in Normal-Form Games}},
author = {Wright, James R. and Leyton-Brown, Kevin},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2010},
pages = {901-907},
doi = {10.1609/AAAI.V24I1.7644},
url = {https://mlanthology.org/aaai/2010/wright2010aaai-beyond/}
}