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On Value-Aligned Cooperative Multi-agent Task Allocation

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Value Engineering in Artificial Intelligence (VALE 2023)

Abstract

Ensuring trustworthy AI and adopting value-aware systems with ethical principles are essential for the harmonious coexistence of humans and intelligent systems. This paper proposes a value-aligned cooperative multi-agent task allocation model for a cooperative whose members jointly own and operate the organization, working towards common goals. The proposed approach instantiates human values into ethical and moral norms. We focus on value awareness through introducing ethical values like justice and fairness into a mathematical programming model for near-optimal multi-agent task allocation. Key performance indicators are modeled using diverse measures in the task sharing context. A simple use-case example demonstrates how value awareness integrates into a decision support system for multi-agent task allocation in a cooperative agri-robot fleet context.

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Acknowledgements

This work has been supported by grant VAE: TED2021-131295B-C33 funded by MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGeneration EU/PRTR”, by grant COSASS: PID2021-123673OB-C32 funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”, and by the AGROBOTS Project of Universidad Rey Juan Carlos funded by the Community of Madrid (Spain), and the IMPULSO Program of the University Rey Juan Carlos.

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Correspondence to Marin Lujak .

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Lujak, M., Fernández, A., Billhardt, H., Ossowski, S., Arias, J., López Sánchez, A. (2024). On Value-Aligned Cooperative Multi-agent Task Allocation. In: Osman, N., Steels, L. (eds) Value Engineering in Artificial Intelligence. VALE 2023. Lecture Notes in Computer Science(), vol 14520. Springer, Cham. https://doi.org/10.1007/978-3-031-58202-8_12

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  • DOI: https://doi.org/10.1007/978-3-031-58202-8_12

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