Toward AI-designed innovation diffusion policies using agent-based simulations and reinforcement learning: The case of digital tool adoption in agriculture

Toward AI-designed innovation diffusion policies using agent-based simulations and reinforcement learning: The case of digital tool adoption in agriculture

In this paper, we tackle innovation diffusion from the perspective of an institution which aims to encourage the adoption of a new product (i.e., an innovation) with mostly social rather than individual benefits. Designing such innovation adoption policies is a very challenging task because of the d...

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Bibliographic Details
Main Authors: Meritxell Vinyals, Regis Sabbadin, Stéphane Couture, Loïc Sadou, Rallou Thomopoulos, Kevin Chapuis, Baptiste Lesquoy, Patrick Taillandier
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Applied Mathematics and Statistics
Subjects:
innovation diffusion
policy design
reinforcement learning
agent-based simulation
deep reinforcement learning
digital agriculture
Online Access:https://www.frontiersin.org/articles/10.3389/fams.2023.1000785/full

Internet

https://www.frontiersin.org/articles/10.3389/fams.2023.1000785/full

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