Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Monsia, Rivaaj, Francon, Olivier, Young, Daniel, Miikkulainen, Risto
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912555499257856
author Monsia, Rivaaj
Francon, Olivier
Young, Daniel
Miikkulainen, Risto
author_facet Monsia, Rivaaj
Francon, Olivier
Young, Daniel
Miikkulainen, Risto
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2508_19173
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems
Monsia, Rivaaj
Francon, Olivier
Young, Daniel
Miikkulainen, Risto
Neural and Evolutionary Computing
Machine Learning
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.
title Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems
topic Neural and Evolutionary Computing
Machine Learning
url https://arxiv.org/abs/2508.19173