How to Find Good Coalitions to Achieve Strategic Objectives

Angelo Ferrando, Vadim Malvone

2023

Abstract

Alternating-time Temporal Logic (ATL) is an extension of the temporal logic CTL in which we can quantify over coalition of agents. In the model checking process, the coalitions in a given formula are fixed, so it is assumed that the user knows the specific coalitions to be checked. Unfortunately, this is not true in general. In this paper, we present an extension of MCMAS, a well-known tool that handles ATL model checking, in which we give the ability to a user to characterise the coalition quantifiers with respect to two main features: the number of agents involved in the coalitions and how to group such agents. Moreover, we give details of such extensions and provide experimental results.

Paper Citation

in Harvard Style

Ferrando A. and Malvone V. (2023). How to Find Good Coalitions to Achieve Strategic Objectives. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-623-1, pages 105-113. DOI: 10.5220/0011778700003393

in Bibtex Style

@conference{icaart23,
author={Angelo Ferrando and Vadim Malvone},
title={How to Find Good Coalitions to Achieve Strategic Objectives},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2023},
pages={105-113},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011778700003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - How to Find Good Coalitions to Achieve Strategic Objectives
SN - 978-989-758-623-1
AU - Ferrando A.
AU - Malvone V.
PY - 2023
SP - 105
EP - 113
DO - 10.5220/0011778700003393