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arXiv · 2310.13072

Reinforcement Learning in Control Theory: A New Approach to Mathematical Problem Solving

Kala Agbo Bidi·Jean-Michel Coron·Amaury Hayat·Nathan Lichtlé
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Abstract

One of the central questions in control theory is achieving stability through feedback control. This paper introduces a novel approach that combines Reinforcement Learning (RL) with mathematical analysis to address this challenge, with a specific focus on the Sterile Insect Technique (SIT) system. The objective is to find a feedback control that stabilizes the mosquito population model. Despite the mathematical complexities and the absence of known solutions for this specific problem, our RL approach identifies a candidate solution for an explicit stabilizing control. This study underscores the synergy between AI and mathematics, opening new avenues for tackling intricate mathematical problems.

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BibTeXRIS

Kala Agbo Bidi, Jean-Michel Coron, Amaury Hayat, Nathan Lichtlé. 2023-10-19. Reinforcement Learning in Control Theory: A New Approach to Mathematical Problem Solving. https://arxiv.org/abs/2310.13072

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