2025/07/13 by Ann Nedime Nese Rende, Rende, Ann Nedime Nese, Tolga Yılmaz +3
Business, Management and Accounting · Engineering · #FOS: Computer and information sciences #FinTech, Crowdfunding, Digital Finance #Multiagent Systems (cs.MA) #Sharing Economy and Platforms #Social and Information Networks (cs.SI) #Transportation and Mobility Innovations
paper · pdf · doi:10.48550/arxiv.2507.09657
openalex publication_date 2025/07/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We use generative agents powered by large language models (LLMs) to simulate a social network in a shared residential building, driving the temperature decisions for a central heating system. Agents, divided into Family Members and Representatives, consider personal preferences, personal traits, connections, and weather conditions. Daily simulations involve family-level consensus followed by building-wide decisions among representatives. We tested three personality traits distributions (positive, mixed, and negative) and found that positive traits correlate with higher happiness and stronger friendships. Temperature preferences, assertiveness, and selflessness have a significant impact on happiness and decisions. This work demonstrates how LLM-driven agents can help simulate nuanced human behavior where complex real-life human simulations are difficult to set.