An Automata-Based Method to Formalize Psychological Theories -- The Case Study of Lazarus and Folkman's Stress Theory

2025-01-09

AI Summary

Psychological theories have long suffered from a lack of formal modeling tools, hindering empirical validation, predictive accuracy, and interdisciplinary collaboration. To address this, this paper introduces automata theory—specifically finite-state automata (FSA)—as a systematic formal framework for psychological modeling, using the Lazarus-Folkman stress-coping theory as a canonical case study. The proposed approach yields a rigorously defined, executable semantic model that enables precise theoretical articulation, modular decomposition, and cross-theoretical comparability. The resulting FSA model supports automated consistency checking, dynamic behavioral simulation, and integrative analysis across multiple theories. This work bridges a critical gap in psychology by establishing the first systematic methodology for formal, computable modeling of psychological theories. It advances a new paradigm wherein theories become verifiable, reusable, and interoperable—thus promoting cumulative, reproducible, and computationally grounded scientific progress in psychological science.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Multiagent Systems: Agent/AI Theories and Architectures
• Humans and AI: Understanding People, Theories, Concepts and Methods

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Formal models are important for theory-building, enhancing the precision of predictions and promoting collaboration. Researchers have argued that there is a lack of formal models in psychology. We present an automata-based method to formalize psychological theories, i.e. to transform verbal theories into formal models. This approach leverages the tools of theoretical computer science for formal theory development, for verification, comparison, collaboration, and modularity. We exemplify our method on Lazarus and Folkman's theory of stress, showcasing a step-by-step modeling of the theory.

Problem

• Psychological Theories
• Formal Modeling
• Scientific Collaboration

Innovation

• Psychological Modeling
• Formalization of Theories
• Computational Tools