Knowledge and Blameworthiness
Artificial Intelligence
2019-03-28 v3 Computer Science and Game Theory
Logic in Computer Science
Abstract
Blameworthiness of an agent or a coalition of agents is often defined in terms of the principle of alternative possibilities: for the coalition to be responsible for an outcome, the outcome must take place and the coalition should have had a strategy to prevent it. In this article we argue that in the settings with imperfect information, not only should the coalition have had a strategy, but it also should have known that it had a strategy, and it should have known what the strategy was. The main technical result of the article is a sound and complete bimodal logic that describes the interplay between knowledge and blameworthiness in strategic games with imperfect information.
Cite
@article{arxiv.1811.02446,
title = {Knowledge and Blameworthiness},
author = {Pavel Naumov and Jia Tao},
journal= {arXiv preprint arXiv:1811.02446},
year = {2019}
}