Axiodynamics: A Nine-Axiom Computational Framework for Affect-Cognition Dynamics

Existing frameworks struggle to formalize non-additive affect-cognition interactions in a computationally tractable way for multi-agent modeling. We introduce axiodynamics, a minimal computational framework based on six core axioms: (1) affective-cognitive non-separability, (2) an appetitive-aversive dyad (Fc/Fi forces), (3) telotopic coherence around an emergent telos, (4) consolidation via moderate contradiction, (5) endo/exo regulation, and (6) nonlinear thresholds. Three methodological axioms (triangulation, multilevel validation, acknowledged incompleteness) frame its epistemic status. Fc/Fi are modeled as intensity- and direction-weighted vectors in a telotopic space, yielding a directional coherence metric (Ntel). A Python pipeline implements these axioms with explicit falsification criteria. Status: This preprint presents a theoretical and methodological proposal. Core parameters are not yet calibrated; validation protocols are pre-registered but not executed. All numerical values are illustrative simulations. The contribution lies in formal transparency, falsifiability, and pre-registered validation architecture—not demonstrated predictive success.