Sentipolis: Emotion-Aware Agents for Social Simulations
- URL: http://arxiv.org/abs/2601.18027v1
- Date: Sun, 25 Jan 2026 22:50:04 GMT
- Title: Sentipolis: Emotion-Aware Agents for Social Simulations
- Authors: Chiyuan Fu, Lyuhao Chen, Yunze Xiao, Weihao Xuan, Carlos Busso, Mona Diab,
- Abstract summary: Sentipolis is a framework for emotionally stateful agents for social simulation.<n>It integrates Pleasure-Arousal-Dominance representation, dual-speed emotion dynamics, and emotion--memory coupling.
- Score: 27.051352819823524
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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