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Severity-sensitive robustness analysis in normative systems

Severity-sensitive robustness analysis in normative systems
Severity-sensitive robustness analysis in normative systems

Norms specify ideal behaviour. Agents, however, are autonomous, and may fail to comply with the ideal. Contrary to Duty obligations can be used to specify reparational behaviour that mitigates the effects of a violation. In addition to specifying reparational behaviours, it is important to understand how robust a system is against possible violations. Depending on what kind of system property we want to preserve, non-compliance with different norms may be of varying severity. We propose a method for analysing robustness of normative systems, with support for Contrary to Duty obligations. We introduce violation severity as a concept orthogonal to reparational behaviour and specify it by means of a partial order over norms. We use this severity partial order, together with normative specifications, to rank the possible worlds from the most to the least compliant. In this way, we are able to use model checking to analyse robustness to a certain severity, or whether it is possible to achieve a certain goal, without violating any norm of a given severity.

0302-9743
72-88
Springer
Gasparini, Luca
15ef6336-0f4e-4acf-8989-c6797c2e6120
Norman, Timothy J.
663e522f-807c-4569-9201-dc141c8eb50d
Kollingbaum, Martin J.
015a7895-2e8f-4e21-a2fc-a2fa1fae37df
Chen, Liang
15459db0-4299-44b7-beaf-fb646add66ac
Telang, Pankaj
Ghose, Aditya
Thangarajah, John
Oren, Nir
Gasparini, Luca
15ef6336-0f4e-4acf-8989-c6797c2e6120
Norman, Timothy J.
663e522f-807c-4569-9201-dc141c8eb50d
Kollingbaum, Martin J.
015a7895-2e8f-4e21-a2fc-a2fa1fae37df
Chen, Liang
15459db0-4299-44b7-beaf-fb646add66ac
Telang, Pankaj
Ghose, Aditya
Thangarajah, John
Oren, Nir

Gasparini, Luca, Norman, Timothy J., Kollingbaum, Martin J. and Chen, Liang (2015) Severity-sensitive robustness analysis in normative systems. Telang, Pankaj, Ghose, Aditya, Thangarajah, John and Oren, Nir (eds.) In Coordination, Organizations, Institutions, and Norms in Agent Systems X - COIN 2014 International Workshops COIN@AAMAS, Revised Selected Papers. vol. 9372, Springer. pp. 72-88 . (doi:10.1007/978-3-319-25420-3_5).

Record type: Conference or Workshop Item (Paper)

Abstract

Norms specify ideal behaviour. Agents, however, are autonomous, and may fail to comply with the ideal. Contrary to Duty obligations can be used to specify reparational behaviour that mitigates the effects of a violation. In addition to specifying reparational behaviours, it is important to understand how robust a system is against possible violations. Depending on what kind of system property we want to preserve, non-compliance with different norms may be of varying severity. We propose a method for analysing robustness of normative systems, with support for Contrary to Duty obligations. We introduce violation severity as a concept orthogonal to reparational behaviour and specify it by means of a partial order over norms. We use this severity partial order, together with normative specifications, to rank the possible worlds from the most to the least compliant. In this way, we are able to use model checking to analyse robustness to a certain severity, or whether it is possible to achieve a certain goal, without violating any norm of a given severity.

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More information

Published date: 2015
Additional Information: Funding Information: This research was sponsored by Selex ES. Publisher Copyright: © Springer International Publishing Switzerland 2015. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.
Venue - Dates: 10th International Conference on Coordination, Organizations, Institutions and Norms in Agent Systems, COIN 2014, , Paris, France, 2016-05-06 - 2016-05-06

Identifiers

Local EPrints ID: 450242
URI: http://eprints.soton.ac.uk/id/eprint/450242
ISSN: 0302-9743
PURE UUID: 3eede263-175a-4884-a269-193bcbabdf6d
ORCID for Timothy J. Norman: ORCID iD orcid.org/0000-0002-6387-4034

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Date deposited: 16 Jul 2021 16:36
Last modified: 18 Mar 2024 03:34

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Contributors

Author: Luca Gasparini
Author: Martin J. Kollingbaum
Author: Liang Chen
Editor: Pankaj Telang
Editor: Aditya Ghose
Editor: John Thangarajah
Editor: Nir Oren

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