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Poster
in
Workshop: MATH-AI: The 3rd Workshop on Mathematical Reasoning and AI

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

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

Keywords: [ Control theory; Reinforcement learning; AI for maths; stabilization; feedback control ]


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. This study underscores the synergy between AI and mathematics, opening new avenues for tackling intricate mathematical problems.

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