[2512.18687] Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model

Computer Science > Artificial Intelligence arXiv:2512.18687 (cs) [Submitted on 21 Dec 2025 (v1), last revised 21 Mar 2026 (this version, v4)] Title:Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model Authors:Yosuke Taniuchi, Chie Hieida, Atsushi Noritake, Kazushi Ikeda, Masaki Isoda View a PDF of the paper titled Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model, by Yosuke Taniuchi and 3 other authors View PDF HTML (experimental) Abstract: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 (...