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Auteurs principaux:	Chakraborty, Pinaki, Caulfield, Tristan, Pym, David
Format:	Preprint
Publié:	2025
Sujets:	Logic in Computer Science Multiagent Systems
Accès en ligne:	https://arxiv.org/abs/2508.01758
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author	Chakraborty, Pinaki Caulfield, Tristan Pym, David
author_facet	Chakraborty, Pinaki Caulfield, Tristan Pym, David
contents	Causal reasoning is essential for understanding decision-making about the behaviour of complex `ecosystems' of systems that underpin modern society, with security -- including issues around correctness, safety, resilience, etc. -- typically providing critical examples. We present a theory of strategic reasoning about system modelling based on minimal structural assumptions and employing the methods of transition systems, supported by a modal logic of system states in the tradition of van Benthem, Hennessy, and Milner, and validated through equivalence theorems. Our framework introduces an intervention operator and a separating conjunction to capture actual causal relationships between component systems of the ecosystem, aligning naturally with Halpern and Pearl's counterfactual approach based on Structural Causal Models. We illustrate the applicability through examples of of decision-making about microservices in distributed systems. We discuss localized decision-making through a separating conjunction. This work unifies a formal, minimalistic notion of system behaviour with a Halpern--Pearl-compatible theory of counterfactual reasoning, providing a logical foundation for studying decision making about causality in complex interacting systems.
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publishDate	2025
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spellingShingle	Causality and Decision-making: A Logical Framework for Systems and Security Modelling Chakraborty, Pinaki Caulfield, Tristan Pym, David Logic in Computer Science Multiagent Systems Causal reasoning is essential for understanding decision-making about the behaviour of complex `ecosystems' of systems that underpin modern society, with security -- including issues around correctness, safety, resilience, etc. -- typically providing critical examples. We present a theory of strategic reasoning about system modelling based on minimal structural assumptions and employing the methods of transition systems, supported by a modal logic of system states in the tradition of van Benthem, Hennessy, and Milner, and validated through equivalence theorems. Our framework introduces an intervention operator and a separating conjunction to capture actual causal relationships between component systems of the ecosystem, aligning naturally with Halpern and Pearl's counterfactual approach based on Structural Causal Models. We illustrate the applicability through examples of of decision-making about microservices in distributed systems. We discuss localized decision-making through a separating conjunction. This work unifies a formal, minimalistic notion of system behaviour with a Halpern--Pearl-compatible theory of counterfactual reasoning, providing a logical foundation for studying decision making about causality in complex interacting systems.
title	Causality and Decision-making: A Logical Framework for Systems and Security Modelling
topic	Logic in Computer Science Multiagent Systems
url	https://arxiv.org/abs/2508.01758

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