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Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems

Chunyan Mu, Muhammad Najib

Shapley values allocate responsibility fairly among agents in stochastic multi-agent games by quantifying retrospective counterfactual impact.

arxiv:2605.13077 v1 · 2026-05-13 · cs.MA · cs.AI

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Claims

C1strongest claim

we utilise the Shapley value and formally show that this method satisfies key desirable properties, including fairness and consistency.

C2weakest assumption

That responsibility attribution in probabilistic multi-agent systems can be fully captured by retrospective counterfactuals within a concurrent stochastic game model without needing domain-specific adjustments beyond the Shapley value.

C3one line summary

Defines retrospective counterfactual responsibility in concurrent stochastic multi-player games, allocates it via Shapley values satisfying fairness and consistency, and uses Nash equilibria for stable responsibility-reward tradeoffs.

References

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[1] Abarca, A.I.R., Broersen, J.M.: A stit logic of responsibility. In: AAMAS. pp. 1717–1719 (2022) 2022
[2] In: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems 2007
[3] MIT Press (2008) 2008
[4] Baier, C., Funke, F., Majumdar, R.: A game-theoretic account of responsibility allocation. In: IJCAI. pp. 1773–1779. ijcai.org (2021) 2021
[5] Baier, C., Funke, F., Majumdar, R.: Responsibility attribution in parameterized markovian models. In: AAAI. pp. 11734–11743. AAAI Press (2021) Counterfactual Reasoning for CR Attribution in Probabilis 2021
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First computed 2026-05-18T03:08:58.748332Z
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Canonical hash

95594fe0276f2747e90d66eea2ce68ab11d4b94d444ddc72967f977e288c49ad

Aliases

arxiv: 2605.13077 · arxiv_version: 2605.13077v1 · doi: 10.48550/arxiv.2605.13077 · pith_short_12: SVMU7YBHN4TU · pith_short_16: SVMU7YBHN4TUP2IN · pith_short_8: SVMU7YBH
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/SVMU7YBHN4TUP2INM3XKFTTIVM \
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Canonical record JSON
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