@inproceedings{
bidi2023reinforcement,
title={Reinforcement Learning in Control Theory: A New Approach to Mathematical Problem Solving},
author={Kala Agbo Bidi and Jean-Michel Coron and Amaury Hayat and Nathan Lichtl{\'e}},
booktitle={The 3rd Workshop on Mathematical Reasoning and AI at NeurIPS'23},
year={2023},
url={https://openreview.net/forum?id=qRu578CgJD}
}
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.
Reinforcement Learning in Control Theory: A New Approach to Mathematical Problem Solving
Kala Agbo Bidi Jean-Michel Coron Amaury Hayat Nathan Lichtlé