Generative Dynamics of Intelligence under Constraints

This work proposes a theoretical framework for understanding intelligence as a generative and constrained dynamical process. Contrary to classical approaches that assume a pre-existing space of possibilities, we show that the space of configurations is itself produced by interacting constraints. Constraints are not treated as passive limitations, but as active operators that generate, structure, and limit the possible. Within this framework, intelligence is no longer defined as a system or a set of states, but as a trajectory evolving in a dynamically generated space of configurations. This trajectory is shaped by constraints that are variable, coupled, and partially incompatible, leading to a fundamental departure from notions of global optimality, stability, and completeness. Instead, intelligence is characterized by its ability to maintain continuity under evolving constraints through local and adaptive compromises. A central contribution of this work is the introduction of generative dynamics under incompatible constraints. Rather than being resolved, incompatibilities act as structural drivers of emergence, forcing the system to explore intermediate configurations. This process produces both possibilities and impossibilities: certain configurations are not merely improbable, but structurally inaccessible. The framework further integrates multiple physical regimes, including quantum, thermodynamic, and information-theoretic constraints. Their coexistence introduces irreducible tensions that prevent global coherence and reinforce the non-closure of the space of possible configurations. As a result, intelligence is inherently non-stationary, path-dependent, and irreversibly embedded in its own history. This leads to a general principle: intelligence can be understood as a trajectory navigating a dynamically generated space of configurations under multiple, incompatible, and evolving constraints, without access to global optimality or complete representation. By shifting the focus from optimization to navigation, and from states to trajectories, this work establishes the foundations for a theory of intelligence grounded in physical constraints, structural limits, and generative dynamics. It opens new perspectives for the analysis of complex systems, artificial intelligence, and the fundamental limits of computation and cognition.