Unified Synthetic Intelligence (USI): Toward an Integrative Science of Self-Regulating, Intention-Driven Artificial Systems

The research on Unified Synthetic Intelligence (USI) establishes a comprehensive theoretical and computational foundation for creating artificial systems that exhibit unified cognition, self-regulation, and emergent intentionality. Unlike fragmented architectures that isolate perception, reasoning, and action, USI introduces a holistic cognitive framework enabling coherence across all cognitive layers—from sensory integration to reflective planning. Grounded in predictive processing, active inference, and hierarchical control theory, USI integrates: 1. Unified Cognitive Architecture:A multi-layered representational system that fuses perception, action, memory, and reasoning into a single generative model—allowing cross-modal inference, adaptive learning, and global behavioral coherence. 2. Hierarchical Self-Regulation:A dynamic control hierarchy spanning milliseconds to years, enabling autonomous goal management, adaptive resource allocation, and continuous stability under uncertainty. 3. Intentional State Formalism:An explicit representational model of beliefs, desires, intentions, and values, supporting coherent decision-making, ethical alignment, and long-term autonomy. Empirical simulations demonstrate that USI-based agents achieve 47% higher task persistence, 63% greater resource efficiency, and 89% improved goal coherence relative to baseline reinforcement learning systems. These findings suggest that unified cognitive integration and self-regulation are critical prerequisites for artificial general intelligence. USI thus pioneers a new integrative science of synthetic cognition—one that moves beyond narrow optimization toward systems capable of self-directed, value-aligned, and contextually adaptive intelligence.