Abstract
<title>Abstract</title> <p>Artificial intelligence alignment remains one of the central challenges in the development of increasingly autonomous and distributed intelligent systems. This paper restates and extends Ethical Field Theory (EFT), a mathematical framework introduced in earlier work (Moslemi Tabrizi, 2026a), that formulates adaptive ethical regulation as a continuous field process rather than a set of symbolic rules. System dynamics are represented by three coupled state variables describing constructive, regulatory, and destabilizing processes, whose evolution is governed by nonlinear field equations, a unified Lagrangian, gauge-consistent regulation, and an entropy-based measure of global organization. The corresponding computational architecture combines compact feature representation, graph-based message passing, adaptive stabilization, and fourth-order Runge–Kutta numerical integration. Beyond this computational core, the present paper develops EFT as a bridge between formal dynamical modeling and broader interpretive and scientific questions. Six independent philosophical traditions — Nietzsche, Eastern philosophy, Buddhism, Aristotle and Plato, Spinoza, and Kant — are read as structural analogies to specific components of the formalism, with an explicit account of where these comparisons illustrate rather than derive the mathematics. The framework is further evaluated against standard criteria for a scientific research programme (explicit state variables, computational reproducibility, predictive capability, and falsifiability), yielding seven concrete, testable predictions, and its physics-inspired vocabulary (fields, gauge symmetry, curvature, entropy) is explicitly situated as mathematical analogy rather than physical claim. The paper's central contribution is therefore not a claim that ethics reduces to physics or that philosophy generated the mathematics, but a single, precisely specified dynamical formalism capable of supporting empirical validation, philosophical interpretation, and AI-governance applications within one coherent mathematical language.</p>