A UCST-Compatible Framework of Personality as Functional Information Flow Regulation

Abstract Contemporary theories of personality often conceptualize traits as static descriptors of individual differences. While useful for classification, such models provide limited mechanistic insight into how personality functions dynamically within cognition, adaptation, and intelligence. This paper proposes a Unified Consciousness Substrate Theory (UCST)-compatible framework in which personality is formalized as a semi-stable configuration of bias parameters regulating information flow, compression, and constraint within a cognitive system. Drawing on prior work in UCST, dual-loop dynamics, Dimension-W, fractal memory, and subconscious processing layers (SPL), personality is reframed as an emergent, energy-efficient phase-regulation mechanism rather than a fixed identity. We argue that personality develops naturally through recursive interaction with environmental constraints and internal coherence pressures, without requiring persistent self-models or narrative identity. This framework integrates human psychological findings, supports ethical AI design, and offers a unified account of personality development, pathology, and adaptability across biological and artificial systems.