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

  • Patricio Julián GerpeEmail author
  • Evangelos Markopoulos
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 965)

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.

Keywords

Agent-based modeling Agent-oriented programming Multi-criteria decision-making TOPSIS Social innovation Interpretable artificial intelligence 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Patricio Julián Gerpe
    • 1
    Email author
  • Evangelos Markopoulos
    • 2
  1. 1.Enpov, Silk LaftoAddis AbabaEthiopia
  2. 2.HULT International Business SchoolLondonUK

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