Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems
This work addresses chlorination control for drinking water management, but it appears incremental as it presents preliminary results from a specific challenge.
The paper tackled the problem of training agents for multi-objective chlorination control in drinking water systems by introducing Evolutionary Surrogate-Assisted Prescription (ESP), with preliminary results showing its potential use in a real-world challenge.
This short, written report introduces the idea of Evolutionary Surrogate-Assisted Prescription (ESP) and presents preliminary results on its potential use in training real-world agents as a part of the 1st AI for Drinking Water Chlorination Challenge at IJCAI-2025. This work was done by a team from Project Resilience, an organization interested in bridging AI to real-world problems.