Physics of Mindful Knowledge

Physics gives a precise account of matter and energy, but it still lacks a general way to describe how knowledge-bearing organization emerges in physical systems and shapes their behavior. The Physics of Mindful Knowledge (PMK) addresses this gap by treating knowledge as instantiated, constraint-bearing structure that stabilizes coherence, supports goal-directed activity, and can be analyzed with the same tools we apply to other physical processes. PMK builds on two key pillars: General Theory of Information (GTI), which formalizes information as a triadic relation (carrier, content, recipient); the Burgin–Mikkilineni Thesis (BMT), which reconceives computation as structural evolution rather than state updates; and Deutsch’s epistemology, which treats knowledge as hard-to-vary explanations and a constructor-level causal resource. Within this framework, a system is “mindful” when it encodes prior knowledge, maintains models of itself and its environment, evaluates its own performance against goals, and adjusts its operations to preserve identity and purpose, all in a naturalistic and testable sense. We develop quantitative signatures for such regimes, including Recovery Effort and Coherence Depth, and translate them into engineering protocols using structural machines (Mindful Machine Architecture) that can be compared experimentally with algorithmic systems under structural, functional, and epistemic perturbations. In doing so, PMK reframes mind and knowledge as regimes of physical organization with measurable effects, offering a practical science of intelligent behavior that remains firmly within the domain of physics and computation.