Verification of multi-agent systems with public actions against strategy logic
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Accepted version
Author(s)
Belardinelli, Francesco
Lomuscio, Alessio
Murano, Aniello
Rubin, Sasha
Type
Journal Article
Abstract
Model checking multi-agent systems, in which agents are distributed and thus may have different observations of the world, against strategic behaviours is known to be a complex problem in a number of settings. There are traditionally two ways of ameliorating this complexity: imposing a hierarchy on the observations of the agents, or restricting agent actions so that they are observable by all agents. We study systems of the latter kind, since they are more suitable for modelling rational agents. In particular, we define multiagent systems in which all actions are public and study the model checking problem of such systems against Strategy Logic with equality, a very rich strategic logic that can express relevant concepts such as Nash equilibria, Pareto optimality, and due to the novel addition of equality, also evolutionary stable strategies. The main result is that the corresponding model checking problem is decidable.
Keywords: Strategy Logic, Multi-agent systems, Imperfect Information, Verification, Formal Methods
Keywords: Strategy Logic, Multi-agent systems, Imperfect Information, Verification, Formal Methods
Date Issued
2020-08
Date Acceptance
2020-05-11
Citation
Artificial Intelligence, 2020, 285, pp.1-29
ISSN
0004-3702
Publisher
Elsevier
Start Page
1
End Page
29
Journal / Book Title
Artificial Intelligence
Volume
285
Copyright Statement
© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Royal Academy Of Engineering
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.sciencedirect.com/science/article/pii/S0004370220300618?via%3Dihub
Grant Number
CIET 1718/26
EP/I00520X/1
Subjects
Artificial Intelligence & Image Processing
0801 Artificial Intelligence and Image Processing
0802 Computation Theory and Mathematics
1702 Cognitive Sciences
Publication Status
Published online
Date Publish Online
2020-05-15