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Modeling Decision-Making with Intelligent Agents to Aid Rural Commuters in Developing Nations

Gerpe, PJ; Markopoulos, E; (2019) Modeling Decision-Making with Intelligent Agents to Aid Rural Commuters in Developing Nations. In: Ahram, T, (ed.) Advances in Artificial Intelligence, Software and Systems Engineering: Proceedings of the AHFE 2019 International Conference on Human Factors in Artificial Intelligence and Social Computing, the AHFE International Conference on Human Factors [...]. (pp. pp. 523-532). Springer: Cham, Switzerland. Green open access

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Abstract

More than a billion rural merchants in the developing world depend on hiring on-demand transportation services to commute people or goods to markets. Selecting the optimal fare involves decision-making characterized by multiple alternatives and competing criteria. Decision support systems are used to solve this. However, those systems are based on object-based approaches which lack the high-level abstractions needed to effectively model and scale human-machine communication. This paper introduces AopifyJS, a novel agent-based decision-support tool. We developed a two-agent simulation. One agent makes a request, then another takes a dataset of a stratified sample of 104 Ethiopian commuter criteria preferences and a dataset of fare alternatives. The second agent computes HPA and TOPSIS algorithms to weight, score, rank those alternatives. Once we run the simulation, it returns an interpretable prescription to the first agent, storing all interactions in an architecture that allows developers to program further customization as interactions scale.

Type: Proceedings paper
Title: Modeling Decision-Making with Intelligent Agents to Aid Rural Commuters in Developing Nations
Event: AHFE 2019 International Conference on Human Factors in Artificial Intelligence and Social Computing etc.
Location: Washington, DC
Dates: 24 July 2019 - 28 July 2019
ISBN-13: 978-3-030-20453-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-20454-9_52
Publisher version: https://doi.org/10.1007/978-3-030-20454-9_52
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Agent-based modeling, Agent-oriented programming, Multi-criteria decision-making, TOPSIS, Social innovation, Interpretable artificial intelligence
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/10120907
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