THE INTERDEPENDENT PROJECTION-ACTION DYNAMICS PRINCIPLE (IPADP): A Conditional, Medium-Agnostic Framework for Interdependent Projection, Action Selection, Realization, and Outcome Classification

AbstractThis paper proposes the Interdependent Projection-Action Dynamics Principle (IPADP), a conditional framework for analyzing systems in which the representation of possible scenarios, selection among candidate actions, realization, and feedback are functionally related. Its primary case is the Mutual-Affection First-Move Inhibition Case (MAFMIC): two individuals may have reciprocal romantic feelings while each remains uncertain about the other's likely response, thereby postponing disclosure despite the possibility of mutual acceptance.The framework distinguishes an operative mechanism from the potentially multiple outcomes associated with its operation. Divergence, contradiction, paradoxical configurations, dilemmas, indecision, inhibition, deadlock, persistence, and resolution are treated as separate analytical categories rather than synonyms for a single mechanism. These categories are not necessarily mutually exclusive, and they do not all represent the same ontological kind of phenomenon.IPADP separates state representation, conditional projection, evaluation, selection, transition, feedback, and outcome classification. It allows a finite number N of interdependent elements and does not presuppose that a particular temporal unit or physical medium is universally necessary. Instead, transfer across media requires an explicit structural mapping that preserves the relevant functional relations.The paper establishes a formal research architecture, defines principal variables, gives a conditional two-agent decision model, describes possible N-system generalizations, and identifies boundary conditions, falsifiable hypotheses, mathematical requirements, and empirical validation procedures. The framework is proposed rather than established as a universal law. Its originality and explanatory advantage must be assessed against existing work in game theory, decision theory, epistemic modelling, dynamical systems, causal inference, and related disciplines.