Some challenges of calibrating differentiable agent-based models

• URL: http://arxiv.org/abs/2307.01085v1
• Date: Mon, 3 Jul 2023 15:07:10 GMT
• Title: Some challenges of calibrating differentiable agent-based models
• Authors: Arnau Quera-Bofarull, Joel Dyer, Anisoara Calinescu, Michael Wooldridge
• Abstract summary: Agent-based models (ABMs) are promising approach to modelling and reasoning about complex systems. Their application in practice is impeded by their complexity, discrete nature, and the difficulty of performing parameter inference and optimisation tasks.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Agent-based models (ABMs) are a promising approach to modelling and reasoning about complex systems, yet their application in practice is impeded by their complexity, discrete nature, and the difficulty of performing parameter inference and optimisation tasks. This in turn has sparked interest in the construction of differentiable ABMs as a strategy for combatting these difficulties, yet a number of challenges remain. In this paper, we discuss and present experiments that highlight some of these challenges, along with potential solutions.

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