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Threat-Aware Capillary Branch Shifting: Adversarial Path Detection, Maneuverability Maximization, and Safe Grafting under Structural Doubt

Authors: Joseph, DeMase;

Threat-Aware Capillary Branch Shifting: Adversarial Path Detection, Maneuverability Maximization, and Safe Grafting under Structural Doubt

Abstract

This paper develops a threat-aware extension of capillary branch navigation in contracting linear systems operating under structural emulation limits. Building on prior work establishing integration capacity (Γ) and emulation deficit (δ), we formalize adversarial path detection in recursive hierarchies where uncertainty arises geometrically rather than from additive disturbance models. We prove that adversarially luring trajectories necessarily induce detectable subsystem violations when projected to sufficiently low integration capacity (Lemma 0; Theorem 1), separating adversarial forcing magnitude from emulation deficit (Lemma 3). A constrained lexicographic graft rule—prioritizing safety, maneuverability, and cumulative deficit— is shown to be uniquely admissible within a formally defined strategy class and resistant to manipulation under structural doubt (Theorem 5). A reserve-to-jump policy with Hold Mode is introduced, and we prove a structural dominance result: when recovery is physically reachable, delaying terminal commitment weakly dominates immediate shutdown (Proposition 8). Numerical simulations verify subsystem density, forcing-chain detection, lexicographic branch selection, and energy-reserve invariance. The results are proved in the linear contracting class. Extensions to nonlinear contraction metrics and full minimax equilibria remain future work.

Keywords

Manipulation resistance, Control under uncertainty, Adversarial control, Stability analysis, Maneuverability maximization, Recursive systems, Emulation deficit, Structural uncertainty, Capacity-separated detection, Option preservation, Integration capacity, Structural doubt, Lexicographic decision rules, Model predictive control, Contracting dynamical systems, Safe decision-making

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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