Year: 2026
Type: preprint
Abstract: Can two implementation processes with the same mean lag give opposite stability predictions for adaptive competition? We show that they can, and quantify the discrepancy. The motivating problem is technological coadaptation: decisions are revised while earlier changes are still being implemented and the competing system continues to change. Configuration updates in adaptive cyber defence and activation of revised algorithmic trading strategies provide concrete settings for this modelling question. A coupled replicator--mutator model separates intended portfolios from those actually in use. Near a uniform interior equilibrium, the interaction geometry determines the feedback branches; under strict antagonism, the largest singular value identifies the first unstable mode. For continuous implementation, hard observation and implementation lags enter through one delay budget. Replacing one smooth implementation filter by periodic partial updates, with zero hard lags and a uniform eligibility-phase calibration, preserves the mean waiting time but lowers the first gain boundary by an explicit positive quadratic correction for short release periods. A reproducible three-strategy benchmark exhibits decay under the continuous model and growth under periodic implementation at the same mean lag and interaction gain. Balanced performance observables can also understate the underlying portfolio oscillations. The results identify a concrete failure of mean-only timing descriptions and provide a benchmark for modelling adaptation and implementation separately.
Source: arXiv (Cornell University)
Author: Omelchenko, Alexander
Institution: University of Bremen
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7167016191
Cites:
Cited by:
Related to: