Predicting Strategic Behavior from Free Text (Extended Abstract)
Omer Ben-Porat, Lital Kuchy, Sharon Hirsch, Guy Elad, Roi Reichart, Moshe Tennenholtz
Abstract
The connection between messaging and action is fundamental both to web applications, such as web search and sentiment analysis, and to economics. However, while prominent online applications exploit messaging in natural (human) language in order to predict non-strategic action selection, the economics literature focuses on the connection between structured stylized messaging to strategic decisions in games and multi-agent encounters. This paper aims to connect these two strands of research, which we consider highly timely and important due to the vast online textual communication on the web. Particularly, we introduce the following question: can free text expressed in natural language serve for the prediction of action selection in an economic context, modeled as a game? We initiate research on this question by providing preliminary positive results.
BibTeX
@inproceedings{ijcai2020p699,
title = {Predicting Strategic Behavior from Free Text (Extended Abstract)},
author = {Ben-Porat, Omer and Kuchy, Lital and Hirsch, Sharon and Elad, Guy and Reichart, Roi and Tennenholtz, Moshe},
booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
Artificial Intelligence, {IJCAI-20}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Christian Bessiere},
pages = {5020--5024},
year = {2020},
month = {7},
note = {Journal track},
doi = {10.24963/ijcai.2020/699},
url = {https://doi.org/10.24963/ijcai.2020/699},
}