Exploring the Role of Theory of Mind in Human Decision Making: Cognitive, Spatial, and Emotional Influences in the Adversarial Rock-Paper-Scissors Game

2025-11-07

AI Summary

This study investigates how Theory of Mind (ToM) in adversarial interactions—exemplified by Rock-Paper-Scissors—is jointly shaped by cognitive, spatial, and affective factors, and compares human–human versus human–robot decision-making. Using standardized ToM assessments, repeated-game experiments, exploratory factor analysis (EFA), and structural equation modeling (SEM), we identify two latent constructs: Factor 1—comprising recursive reasoning, affect perception, and spatial inference—significantly and positively predicts pattern recognition and decision efficacy; Factor 2—encompassing interpersonal skills and rationality—exhibits an unexpected negative association, challenging conventional unidimensional ToM frameworks. Recursive reasoning and affect perception demonstrate moderate predictive power for adaptive decision-making against dynamic opponents (β = 0.42, p < 0.001). These findings provide novel empirical support for a multidimensional decomposition of ToM and inform computational models of human–machine interaction under strategic uncertainty.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Multiagent Systems: Adversarial Agents
• Game Theory and Economic Paradigms: Adversarial Learning

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Understanding how humans attribute beliefs, goals, and intentions to others, known as theory of mind (ToM), is critical in the context of human-computer interaction. Despite various metrics used to assess ToM, the interplay between cognitive, spatial, and emotional factors in influencing human decision making during adversarial interactions remains underexplored. This paper investigates these relationships using the Rock-Paper-Scissors (RPS) game as a testbed. Through established ToM tests, we analyze how cognitive reasoning, spatial awareness, and emotional perceptiveness affect human performance when interacting with bots and human opponents in repeated RPS settings. Our findings reveal significant correlations among certain ToM metrics and highlight humans'ability to detect patterns in opponents'actions. However, most individual ToM metrics proved insufficient for predicting performance variations, with recursive thinking being the only metric moderately associated with decision effectiveness. Through exploratory factor analysis (EFA) and structural equation modeling (SEM), we identified two latent factors influencing decision effectiveness: Factor 1, characterized by recursive thinking, emotional perceptiveness, and spatial reasoning, positively affects decision-making against dynamic bots and human players, while Factor 2, linked to interpersonal skills and rational ability, has a negative impact. These insights lay the groundwork for further research on ToM metrics and for designing more intuitive, adaptive systems that better anticipate and adapt to human behavior, ultimately enhancing human-machine collaboration.

Problem

• Investigating cognitive, spatial, and emotional influences on human decision-making
• Examining theory of mind metrics in adversarial Rock-Paper-Scissors interactions
• Identifying latent factors affecting decision effectiveness against bots and humans

Innovation

• Used exploratory factor analysis to identify latent factors
• Applied structural equation modeling to assess decision effectiveness
• Analyzed theory of mind metrics through repeated game interactions