The function is designed for real-time computation and can be integrated into multi-agent simulations, social network analyses, or behavioral monitoring tools.
Temporal smoothing or decay factors may be introduced to prevent short-term volatility from dominating long-term relational patterns.
Incorporation of machine learning estimators for dynamic wkw_k and context-dependent recalibration of CC may further increase the model's responsiveness and robustness.
B. Variable Definitions, Weights, and Justifications
The relational scoring function introduced in Section 4.A,
Rij(t)=k=1nwkVk,ij(t)+CR_{ij}(t) = \sum_{k=1}^n w_k \cdot V_{k,ij}(t) + C
provides a time-sensitive, additive aggregation of multiple interactional variables, each representing a critical dimension of the relational ecosystem. Below we define the core variables Vk,ij(t)V_{k,ij}(t), assign weights wkw_k based on theoretical significance and empirical sensitivity, and justify their inclusion within the model. Each variable captures a distinct aspect of social cognition, emotion, behavior, or perception relevant to the dynamics of relational trust and strategy.
Primary Relational Variables
Symbol
Variable Name
Description
Theoretical Basis
Suggested Weight Range (wkw_k)
