Artificial ontogeny, developmental encodings, robot reproduction, and inherited controllers are established research directions, yet a narrower question remains: can a newborn artificial agent exhibit measurable biparental heredity before learning, and can that dependence be isolated causally rather than inferred only...
Digital twins are increasingly used for smart-building monitoring and control, yet many evaluations focus on state estimation or fault detection rather than whether sensing errors materially affect closed-loop outcomes. This paper introduces a ground-truth-aware simulation framework that separates the latent physical s...
The results show strong asymmetry in modality use: the processed-language pathway is strongly associated with prediction quality, while the current RGB pathway provides no aggregate error advantage, and the results characterize the fixed pilot subset and executed protocol rather than full-benchmark training.
L. S. Saoud, Oualid Doukhi, E. Reihani et al.· 0 citations
S Settling is introduced, an equilibrium-based inference operator that separates proposal generation, consistency evaluation, and test-time equilibrium selection and establishes exact-gradient descent, local convergence, and an inexact-gradient robustness condition relevant to learned consistency critics.
Distributed Spectrum Compliance and Orchestration (DISCO) is introduced, a hierarchical architecture that separates local spectrum learning from edge-level compliance regulation and slower cloud or non-terrestrial-network context adaptation.
L. S. Saoud, Moussa Ayyash· arXiv.org· 0 citations
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