Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model
Social comparison$\unicode{x2014}$the process of evaluating one's rewards relative to others$\unicode{x2014}$is an essential feature of social emotions such as envy and plays a fundamental role in primate social cognition. However, it remains unknown how information about others' rewards affects one's own reward valuation. This study examines whether monkeys merely recognize objective differences in reward or instead infer others' subjective reward valuations. To address this issue, a constructive approach$\unicode{x2014}$one that replicates target emotions in artificial systems and extracts knowledge from them$\unicode{x2014}$was employed, owing to its potential to simulate how the monkey interacts with social contexts, specifically social comparison. We developed three computational models with varying degrees of social information processing: an Internal Prediction Model (IPM), which infers the partner's subjective values; a No Comparison Model (NCM), which disregards partner information; and an External Comparison Model (ECM), which directly incorporates the partner's objective rewards. We trained the models on a dataset containing the behavior of a pair of monkeys, their rewards, and the conditioned stimuli, and then evaluated the models' ability to classify subjective values across pre-defined experimental conditions. The ECM achieved the best classification result (0.88 for the ECM vs. 0.85 for the IPM on the Rand index), suggesting that, in our modeling framework, social comparison relies on objective differences in reward rather than on inferences about subjective reward values.