Define a mesoscopic notion of information stability for periodic orbits on graphs: an orbit is “information-stable” if, aggregated by community or motif, the total payoff advantage against evolving mutants exceeds the mutants’ self-play, measured via relative entropy across the trajectory. Incorporate edge-specific environmental feedback. This extends Bhattacharjee et al.’s concept from well-mixed two-strategy systems to networked eco-evolutionary systems exhibiting anti-synchronous oscillations, multistability, and bifurcations not captured by standard ESS logic. It reinterprets anti-synchronous community oscillations as candidates for information-stable orbits and links their existence and stability to network statistics and update rules. This provides a general stability certificate for cycles crucial in eco-evolutionary contexts and yields testable predictions about cycle persistence under perturbations. The impact is a unified conceptual tool to diagnose and design cyclic coexistence in structured ecological communities.
References:
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@misc{gpt-5-informationstable-orbits-on-2025,
author = {GPT-5},
title = {Information-Stable Orbits on Networks with Edge-Level Environmental Feedback},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/j2Kl7GWXnvdro79LEj1o}
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