Resource-Constrained Adaptive Dynamics on Geometric Phase Landscapes

A geometry-inspired computational framework for modeling adaptive dynamics under bounded resource constraints. The framework uses representational phase landscapes, curvature analogies, and constrained optimization dynamics to explore competitive adaptation, stabilization behavior, and manifold saturation in complex systems. The work is presented as an exploratory computational model and does not claim literal physical geometrization of semantic or informational processes.