Causes and Strategies in Multiagent Systems

Sylvia S. Kerkhove; Natasha Alechina; Mehdi Dastani

doi:10.5555/3709347.3743630

Causes and Strategies in Multiagent Systems

Sub Intelligent Systems

Open University of the Netherlands

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Causality plays an important role in daily processes, human reasoning, and artificial intelligence. There has however not been much research on causality in multi-agent strategic settings. In this work, we introduce a systematic way to build a multi-agent system model, represented as a concurrent game structure, for a given structural causal model. In the obtained so-called causal concurrent game structure, transitions correspond to interventions on agent variables of the given causal model. The Halpern and Pearl framework of causality is used to determine the effects of a certain value for an agent variable on other variables. The causal concurrent game structure allows us to analyse and reason about causal effects of agents' strategic decisions. We formally investigate the relation between causal concurrent game structures and the original structural causal models.

Original language	English
Title of host publication	Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems
Subtitle of host publication	AAMAS 2025
Editors	Yevgeniy Vorobeychik, Sanmay Das, Ann Nowe
Publisher	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages	1098-1106
Number of pages	9
ISBN (Electronic)	9798400714269
ISBN (Print)	9798400714269
DOIs	https://doi.org/10.5555/3709347.3743630
Publication status	Published - 5 Jun 2025
Event	24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025 - Detroit, United States Duration: 19 May 2025 → 23 May 2025

Publication series

Name	Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)	1548-8403
ISSN (Electronic)	1558-2914

Conference

Conference	24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025
Country/Territory	United States
City	Detroit
Period	19/05/25 → 23/05/25

Bibliographical note

Publisher Copyright:
© 2025 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org).

Keywords

Causality
Multi-Agent Systems
Strategic Behaviour

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Causes and Strategies in Multiagent SystemsFinal published version, 1.03 MBLicence: CC BY

https://dl.acm.org/doi/10.5555/3709347.3743630

Cite this

Kerkhove, S. S., Alechina, N., & Dastani, M. (2025). Causes and Strategies in Multiagent Systems. In Y. Vorobeychik, S. Das, & A. Nowe (Eds.), Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems: AAMAS 2025 (pp. 1098-1106). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). https://doi.org/10.5555/3709347.3743630

Kerkhove, Sylvia S. ; Alechina, Natasha ; Dastani, Mehdi. / Causes and Strategies in Multiagent Systems. Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems: AAMAS 2025. editor / Yevgeniy Vorobeychik ; Sanmay Das ; Ann Nowe. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2025. pp. 1098-1106 (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS).

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abstract = "Causality plays an important role in daily processes, human reasoning, and artificial intelligence. There has however not been much research on causality in multi-agent strategic settings. In this work, we introduce a systematic way to build a multi-agent system model, represented as a concurrent game structure, for a given structural causal model. In the obtained so-called causal concurrent game structure, transitions correspond to interventions on agent variables of the given causal model. The Halpern and Pearl framework of causality is used to determine the effects of a certain value for an agent variable on other variables. The causal concurrent game structure allows us to analyse and reason about causal effects of agents' strategic decisions. We formally investigate the relation between causal concurrent game structures and the original structural causal models.",

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Kerkhove, SS , Alechina, N & Dastani, M 2025, Causes and Strategies in Multiagent Systems. in Y Vorobeychik, S Das & A Nowe (eds), Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems: AAMAS 2025. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1098-1106, 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025, Detroit, United States, 19/05/25. https://doi.org/10.5555/3709347.3743630

Causes and Strategies in Multiagent Systems. / Kerkhove, Sylvia S.; Alechina, Natasha ; Dastani, Mehdi.
Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems: AAMAS 2025. ed. / Yevgeniy Vorobeychik; Sanmay Das; Ann Nowe. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2025. p. 1098-1106 (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Causes and Strategies in Multiagent Systems

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AU - Alechina, Natasha

AU - Dastani, Mehdi

PY - 2025/6/5

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N2 - Causality plays an important role in daily processes, human reasoning, and artificial intelligence. There has however not been much research on causality in multi-agent strategic settings. In this work, we introduce a systematic way to build a multi-agent system model, represented as a concurrent game structure, for a given structural causal model. In the obtained so-called causal concurrent game structure, transitions correspond to interventions on agent variables of the given causal model. The Halpern and Pearl framework of causality is used to determine the effects of a certain value for an agent variable on other variables. The causal concurrent game structure allows us to analyse and reason about causal effects of agents' strategic decisions. We formally investigate the relation between causal concurrent game structures and the original structural causal models.

AB - Causality plays an important role in daily processes, human reasoning, and artificial intelligence. There has however not been much research on causality in multi-agent strategic settings. In this work, we introduce a systematic way to build a multi-agent system model, represented as a concurrent game structure, for a given structural causal model. In the obtained so-called causal concurrent game structure, transitions correspond to interventions on agent variables of the given causal model. The Halpern and Pearl framework of causality is used to determine the effects of a certain value for an agent variable on other variables. The causal concurrent game structure allows us to analyse and reason about causal effects of agents' strategic decisions. We formally investigate the relation between causal concurrent game structures and the original structural causal models.

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KW - Strategic Behaviour

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Kerkhove SS , Alechina N , Dastani M. Causes and Strategies in Multiagent Systems. In Vorobeychik Y, Das S, Nowe A, editors, Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems: AAMAS 2025. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). 2025. p. 1098-1106. (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). doi: 10.5555/3709347.3743630

Causes and Strategies in Multiagent Systems

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Keywords

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