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Towards Explainable Recommendations of Resource Allocation Mechanisms in On-Demand Transport Fleets

Abstract : Multi-agent systems can be considered a natural paradigm when modeling various transportation systems, whose management involves solving hard, dynamic, and distributed allocation problems. Such problems have been studied for decades, and various solutions have been proposed. However, even the most straightforward resource allocation mechanisms lead to debates on efficiency vs. fairness, business quality vs. user experience, or performance vs. robustness. We aim to design an analytical tool that functions as a recommendation system for on-demand transport (ODT) authorities. This tool recommends specific allocation mechanisms that match the authority's objectives and preferences to solve allocation problems for particular contextual scenarios. The paper emphasizes the need for transparency and explainability of resource allocation decisions in ODT systems to be understandable by humans and move toward a more controllable resource allocation. We propose a multi-agent architecture to meet these requirements.
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https://hal-emse.ccsd.cnrs.fr/emse-03186967
Contributor : Alaa Daoud <>
Submitted on : Wednesday, March 31, 2021 - 3:12:48 PM
Last modification on : Friday, July 16, 2021 - 2:33:23 PM

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Alaa Daoud, Hiba Alqasir, Yazan Mualla, Amro Najjar, Gauthier Picard, et al.. Towards Explainable Recommendations of Resource Allocation Mechanisms in On-Demand Transport Fleets. Explainable and Transparent AI and Multi-Agent Systems, Third International Workshop (EXTRAAMAS 2021), May 2021, London-UK (ONLINE), United Kingdom. pp.97--115, ⟨10.1007/978-3-030-82017-6_7⟩. ⟨emse-03186967⟩

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