Work

Distributed Evolutionary Algorithms with Adversarial Corruption

Year: 2025

Type: conference-paper

Abstract: Evolutionary algorithms are inherently parallel optimization methods that have been successfully applied to many critical systems. While our understanding of their performance has steadily progressed, most existing work on distributed evolution assumes a perfect runtime environment. This assumption does not always hold in practice, and it is important to consider how robust such systems are to attack.

DOI: 10.1145/3729878.3746622

Authors: Brahim Aboutaib, Andrew M. Sutton

Institution: University of Minnesota, Duluth

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funder: Universitas Brawijaya

Award: G7392981063

OpenAlex ID: W4413311680

FWCI: 1.006

Cites: 38

Cited by: 1

Related to: 10