Classical mechanics and gradient-based optimization share a flaw: they assumegreedy motion along −∇L. In reality, physical and computational systems deviate,dissipate, and explore.We propose a generalization governed by deviational dynamics. We introducefour elements: inertia Cm, dissipation Dz , a warping function w(x, t) that warpsthe gradient, and the 3D Balance Force B(x, t) that encodes anticipatory avoidanceand self-correction.These combine into the Balance Law of Motion. We prove that Newton’sF = ma and damped gradient flow are special cases (B = 0, w = 1), and thatdeviation is the third paradigm of motion. We illustrate without lab measurement:(i) anticipatory obstacle avoidance, (ii) escape from local minima. Finally, we showthat irreversible time > 0 emerges iff B(x, t)̸ = 0.The physical origin of w(x, t) is deferred to future work.
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DR. ZULFIQAR ALI KHAN (2026) studied this question.
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