# Sentipolis: Emotion-Aware Agents for Social Simulations Source: [Sentipolis: Emotion-Aware Agents for Social Simulations]() Collection index: [llms.txt]() Data updated: 2026-04-23T05:00:05.534Z Authors: Chiyuan Fu, Lyuhao Chen, Yunze Xiao, Weihao Xuan, Carlos Busso, Mona Diab Published: 2026-01-25T22:50:04.000Z ## Abstract LLM agents are increasingly used for social simulation, yet emotion is often treated as a transient cue, causing emotional amnesia and weak long-horizon continuity. We present Sentipolis, a framework for emotionally stateful agents that integrates continuous Pleasure-Arousal-Dominance (PAD) representation, dual-speed emotion dynamics, and emotion--memory coupling. Across thousands of interactions over multiple base models and evaluators, Sentipolis improves emotionally grounded behavior, boosting communication, and emotional continuity. Gains are model-dependent: believability increases for higher-capacity models but can drop for smaller ones, and emotion-awareness can mildly reduce adherence to social norms, reflecting a human-like tension between emotion-driven behavior and rule compliance in social simulation. Network-level diagnostics show reciprocal, moderately clustered, and temporally stable relationship structures, supporting the study of cumulative social dynamics such as alliance formation and gradual relationship change. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Social Intelligence Evaluation on SENTIPOLIS v1 (test)](): Social Intelligence Evaluation; SENTIPOLIS v1 (test); Empathy (EMP): 7.072. ## Original sources and implementation [Original paper]() [PDF]()