by carolchu1208 · 未分类 · ★ 14
LLM-Based Multi-Agent System for Simulating and Analyzing Marketing and Consumer Behavior 📄 Paper: arXiv:2510.18155 | PDF 📖 Abstract This repository implements a multi-LLM generative agent framework for simulating consumer decision-making and analyzing marketing strategies in virtual environments. Building on the foundational Generative Agents framework by Park et al. (2023), we extend LLM-powered simulations from general human behavior to the specialized domain of marketing and consumer behavior.
| Stars | 14 |
| Forks | 3 |
| Language | Python |
| Category | 未分类 |
| Quality Score | 26.2/100 |
| Last Updated | 2026-04-14 |
| Created | 2025-07-16 |
| Platforms | python |
| Est. Tokens | ~91k |
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LLM-Based-Generative-Agents-Simulating-Consumer-Decisions is LLM-Based Generative Agents: Simulating Consumer Decisions and Social Interaction Under Price Discount Strategies. It is categorized as a 未分类 with 14 GitHub stars.
LLM-Based-Generative-Agents-Simulating-Consumer-Decisions is primarily written in Python.
You can find installation instructions and usage details in the LLM-Based-Generative-Agents-Simulating-Consumer-Decisions GitHub repository at github.com/carolchu1208/LLM-Based-Generative-Agents-Simulating-Consumer-Decisions. The project has 14 stars and 3 forks, indicating an active community.