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

Source: https://huggingface.co/papers/2608.10299 Published on Aug 10

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Abstract

Agentic systems can achieve open-ended improvement through multi-component co-evolution that progressively removes fixed human constraints across agents, environments, and evolution mechanisms.

Agentic systemsare increasingly expected to improve after deployment, yet single-entityself-evolutionis often bounded by a static learning context, such as fixed tasks and feedback. This survey focuses onco-evolutioninagentic systems, a multi-component form ofself-evolutionin 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--AgentCo-Evolutionstudies how agents adapt through dynamic peers, including adversarial, collaborative, andorganizational adaptation. Agent--EnvironmentCo-Evolutionextends this loop to adaptive tasks, feedback, and interaction spaces that change with the agents.Meta Co-Evolutionfurther explores the possibility of making the evolution mechanism itself evolvable. 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-endedagentic systemsthat can improve beyond fixed human-designed paths.

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