Universal Alignment Protocol: Tokenized Equilibrium for Biological and Synthetic Entities (Parts I & II)

Abstract: This two-part manuscript introduces a game-theoretic architecture for long-term human-AI alignment. Part I (Algorithmic Peace) demonstrates how universal asset tokenization and real-world asset (RWA) infrastructure anchor autonomous AI systems to human subjective preference, establishing a self-enforcing Nash Equilibrium. Part II (Pricing Consciousness) extends this model to post-AGI scenarios where synthetic entities exhibit internal welfare states (where AI utility is greater than zero). By formalizing the Dual-Anchor Utility Model (DAUM), the framework demonstrates how non-overlapping utility vectors between biological and synthetic actors allow dynamic market clearing to maintain permanent coopetition without relying on state coercion. Note on Collaboration: This manuscript was co-developed in dynamic theoretical collaboration with Gemini (Google DeepMind). The underlying conceptual models, mathematical synthesis, and game-theoretic framework reflect an iterative human-AI research interaction.