Structural Resonance Theory (SRT) Finger IV — Constraint Spaces, Intelligence, and the Scaling of Cognitive Power

This paper formalizes planning and insight as emergent phenomena arising from structural reconfiguration within finite, dynamically constrained cognitive spaces. Departing from representational, search-based, and optimization-centric accounts, it advances a non-teleological framework in which planning is understood as pre-stabilized trajectory biasing and insight as a topological discontinuity in the navigable configuration space of a system. Rather than modeling cognition as symbol manipulation or utility maximization, the framework treats intelligent behavior as the modulation of constraint weights governing accessible transitions. The paper introduces a geometric account of insight in which sudden problem-solving breakthroughs correspond to discrete changes in connectivity—specifically, the emergence or dissolution of connected components within the system’s effective constraint graph. These transitions are not gradual accumulations of information but phase-like reconfigurations driven by internal constraint relaxation, reweighting, or resonance alignment. This explains the phenomenology of “Aha” moments, their abruptness, and their resistance to introspective reconstruction. Planning, on this account, is not foresight over an objective future state space but the stabilization of local directional bias under bounded uncertainty. Plans are temporary constraint alignments that shape near-term trajectories without implying global optimality, convergence, or teleological direction. The paper demonstrates how planning failure, rigidity, and overcommitment arise when constraint weights become prematurely stabilized, reducing navigable volume and suppressing adaptive reconfiguration. The framework yields multiple falsifiable predictions distinguishing it from dominant models, including discontinuous signatures in behavioral latency distributions, measurable changes in topological invariants of neural or behavioral state-space reconstructions surrounding insight events, and characteristic failure modes under artificially induced constraint fixation. By grounding planning and insight in constraint geometry rather than representational content, the paper provides a unified, non-teleological account of intelligent discontinuity consistent with finite physical substrates and open-ended exploration.