Weighted Coherence Model: A State-Based Alternative to Priority-Driven Cognition

The Weighted Coherence Model (WCM) introduces a state-based alternative to priority-driven cognition and decision-making.Instead of selecting among competing options through hierarchical prioritization, the model represents cognition as a dynamically constrained distribution of epistemic weight across multiple interpretative fields. At any moment, the system maintains a conserved total of epistemic weight, which is continuously redistributed in response to contextual change, internal tension, and structured antagonism between incompatible interpretations. Decisions and actions do not arise from choice or exclusion, but from the stabilization of the global coherence state. The model provides a formal framework for understanding ambiguity, ambivalence, and interpretive overload without collapse into premature resolution. It offers a principled explanation for phenomena such as hallucination, drift, and instability in generative systems, while remaining equally applicable to human cognition and complex decision environments. This work presents the conceptual foundations, formal constraints, and cognitive interpretation of weighted coherence, proposing a non-prioritized paradigm for reasoning under uncertainty.