Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

PhD Qualifying Examination


Title: "Co-Evolution in Agentic Systems: Toward Self-Directed Evolution 
Beyond Human Design"

by

Miss Qing ZONG


Abstract:

Agentic systems are increasingly expected to improve after deployment, yet 
single-entity self-evolution is often bounded by a static learning context, 
such as fixed tasks and feedback. This survey focuses on co-evolution in 
agentic systems, a multi-component form of self-evolution in which multiple 
agents and their environment impose adaptive pressure on one another. To 
organize existing papers, we propose a progressive three-stage taxonomy that 
traces how the system gradually sheds human-engineered constraints. 
Agent--Agent Co-Evolution studies how agents adapt through dynamic peers, 
including adversarial, collaborative, and organizational adaptation. 
Agent--Environment Co-Evolution extends this loop to adaptive tasks, 
feedback, and interaction spaces that change with the agents. Meta 
Co-Evolution further explores the possibility of making the evolution 
mechanism itself evolvable based on related pioneering papers. We also 
discuss open challenges in evaluating such systems, scaling them across 
multiple components, and keeping increasingly autonomous evolutionary 
processes safe and controllable. This survey provides a unified foundation 
for building robust and open-ended agentic systems that can improve beyond 
fixed human-designed paths.


Date:                   Thursday, 23 July 2026

Time:                   9:00am - 11:00am

Venue:                  Room 3494
                        Lift 25/26

Committee Members:      Dr. Yangqiu Song (Supervisor)
                        Dr. May Fung (Chairperson)
                        Dr. Xiaomin Ouyang