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Description
This works examines the Allison Mixture concept- an extension of Parrondo's Paradox-that generates sequences with significant autocovariance by combining two initially uncorrelated processes. The major objective is to validate the Allison Mixture formula, which has not been fully proven in its general applicability. This research builds upon prior studies, comparing autocovariance results derived from traditional statistical methods with those obtained through Monte Carlo simulations applied to the Entrance-Deterrence game. Although complete verification was not achieved, the experiments identified particular optimal conditions under which the formula functioned effectively. The results highlight the efficacy of the Allison Mixture methodology in formulating adaptive solutions inside dynamic environments, where conventional methods may insufficiently identify fundamental patterns and correlations.
