A Computational Model of Ostrom's Institutional Analysis and Development Framework (Extended Abstract)
Abstract
Ostrom's Institutional Analysis and Development (IAD) framework represents a comprehensive theoretical effort to identify and outline the variables that determine the outcome in any social interaction. Taking inspiration from it, we define the Action Situation Language (ASL), a machine-readable logical language to express the components of a multiagent interaction, with a special focus on the rules adopted by the community. The ASL is complemented by a game engine that takes an interaction description as input and automatically grounds its semantics as an Extensive-Form Game (EFG), which can be readily analysed using standard game-theoretical solution concepts. Overall, our model allows a community of agents to perform what-if analysis on a set of rules being considered for adoption, by automatically connecting rule configurations to the outcomes they incentivize.
Cite
Text
Montes et al. "A Computational Model of Ostrom's Institutional Analysis and Development Framework (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2023. doi:10.24963/IJCAI.2023/786Markdown
[Montes et al. "A Computational Model of Ostrom's Institutional Analysis and Development Framework (Extended Abstract)." International Joint Conference on Artificial Intelligence, 2023.](https://mlanthology.org/ijcai/2023/montes2023ijcai-computational/) doi:10.24963/IJCAI.2023/786BibTeX
@inproceedings{montes2023ijcai-computational,
title = {{A Computational Model of Ostrom's Institutional Analysis and Development Framework (Extended Abstract)}},
author = {Montes, Nieves and Osman, Nardine and Sierra, Carles},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2023},
pages = {6937-6941},
doi = {10.24963/IJCAI.2023/786},
url = {https://mlanthology.org/ijcai/2023/montes2023ijcai-computational/}
}