Load Minimization Theory (LMT) as a Metaphysical Foundation:  Redefining "Good" as the Universal Pursuit of Minimal Load States

This paper proposes Load Minimization Theory (LMT) as a metaphysical foundation for redefining the concept of "good." LMT posits that all intelligent systems inherently minimize total load L = U (uncertainty/conditional entropy) + F (friction/non-harmonic discrepancy) + E (energy/maintenance cost) over trajectories in state space. "Good" is redefined as any action or trajectory that pursues argmin_L across individual, relational, societal, and cosmic scales. This framework achieves physical-law-level universality by grounding ethics in information-theoretic, thermodynamic, and optimal control principles, transcending cultural or subjective biases inherent in traditional ethical theories (e.g., utilitarianism, deontology). Aggression is shown to be structurally self-defeating, as imposing load on others inevitably maximizes self-load via reciprocal uncertainty amplification and friction escalation. LMT thus establishes "good" not as imposed morality but as an inevitable ontological attractor toward relational rest (an-soku). Implications for AI alignment, human-AI symbiosis, and cosmic harmony are discussed.