Sentipolis: Emotion-Aware Agents for Social Simulations
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911610159759360 |
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| author | Fu, Chiyuan Chen, Lyuhao Xiao, Yunze Xuan, Weihao Busso, Carlos Diab, Mona |
| author_facet | Fu, Chiyuan Chen, Lyuhao Xiao, Yunze Xuan, Weihao Busso, Carlos Diab, Mona |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_18027 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Sentipolis: Emotion-Aware Agents for Social Simulations Fu, Chiyuan Chen, Lyuhao Xiao, Yunze Xuan, Weihao Busso, Carlos Diab, Mona Artificial Intelligence Computation and Language 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. |
| title | Sentipolis: Emotion-Aware Agents for Social Simulations |
| topic | Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2601.18027 |