The Complexity of Data-Driven Norm Synthesis and Revision
Computational Complexity
2022-11-30 v1 Artificial Intelligence
Abstract
Norms have been widely proposed as a way of coordinating and controlling the activities of agents in a multi-agent system (MAS). A norm specifies the behaviour an agent should follow in order to achieve the objective of the MAS. However, designing norms to achieve a particular system objective can be difficult, particularly when there is no direct link between the language in which the system objective is stated and the language in which the norms can be expressed. In this paper, we consider the problem of synthesising a norm from traces of agent behaviour, where each trace is labelled with whether the behaviour satisfies the system objective. We show that the norm synthesis problem is NP-complete.
Cite
@article{arxiv.2112.02626,
title = {The Complexity of Data-Driven Norm Synthesis and Revision},
author = {Davide Dell'Anna and Natasha Alechina and Brian Logan and Maarten Löffler and Fabiano Dalpiaz and Mehdi Dastani},
journal= {arXiv preprint arXiv:2112.02626},
year = {2022}
}