This paper develops a dynamical formulation of action within the Reasoning Turing Machine (RTM) framework. Action is modeled as the result of force equilibrium in an epistemic manifold, where multiple structured drives interact under behavioral gating. A continuous-time law of behavior formation is derived, showing how coherent action emerges from internal force balance rather than reward maximization. Stability properties and admissibility conditions are analyzed within a nonlinear dynamical systems perspective. This work constitutes the second component of a trilogy, extending the energy-based coherence principle introduced in Empathy Energy Minimization and preparing the formal groundwork for long-term stabilization in Gödel Memory.