Abstract
Supply chains exhibit complex dynamics and intricate dependencies among their components, whose understanding is crucial for addressing the challenges highlighted by recent global disruptions. This paper presents a novel multi-agent system designed to simulate supply chains, linking reasoning about dynamic domains and multi-agent systems to reasoning about the high-level primitives of the NIST CPS Framework. Our approach synthesizes existing research on supply chain formalization and integrates these insights with multi-agent techniques, employing a declarative approach to model interactions and dependencies. The simulation framework models a set of autonomous agents within a partially observable environment, and whose interactions are dictated by contracts. The system dynamically reconciles agents’ actions, assessing their feasibility and consequences. Based on the state of the domain, the simulation framework also draws conclusions about the high-level notions of requirements and concerns of the NIST CPS Framework, which provide a uniform and domain-agnostic vocabulary for the understanding of such complex systems as supply chains.
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Notes
- 1.
In general, \(\psi \) and \(\varphi \) can be fluent formulas. For the purpose of this paper, it suffices that conjunctions are considered.
- 2.
The predicate \(\mathtt {conflict(L,L')}\) can be defined for domains with static causal laws. In our case study, we need to deal with numeric fluents and thus will need some rules preventing a fluent be assigned two different values at the same time by different actions.
- 3.
- 4.
- 5.
The Belief-Desire-Intention architecture includes reasoning about beliefs (updating beliefs given an observed event), goals (deciding on what to achieve given the desires), and plans (how to achieve the goal) [4].
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Portions of this publication and research effort are made possible through the help and support of NIST via cooperative agreement 70NANB21H167.
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Tran, L., Son, T.C., Flynn, D., Balduccini, M. (2025). A Simulation for Supply Chains Contract Execution. In: Dodaro, C., Gupta, G., Martinez, M.V. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2024. Lecture Notes in Computer Science(), vol 15245. Springer, Cham. https://doi.org/10.1007/978-3-031-74209-5_25
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