Can LLMs boost creativity in multi-agent systems?
Creative Agents: Simulating the Systems Model of Creativity with Generative Agents
This paper explores whether multi-agent systems can enhance the "creativity" of generative AI models, specifically in art generation. It simulates Csikszentmihalyi's systems model of creativity using LLMs (Gemini) for text and critique generation and Stable Diffusion for image generation. Virtual artists receive feedback from virtual critics, influencing their subsequent artwork and the overall domain trends.
Key points for LLM-based multi-agent systems: LLMs can effectively simulate human-like agents in creative domains, allowing for the study of social dynamics' influence on creative output. Feedback mechanisms between agents drive iterative refinement and potential creative growth, though challenges remain in aligning visual output with descriptive text prompts and preventing LLM outputs from becoming repetitive or nonsensical due to overly abstract prompts. The systems model offers a framework for structuring multi-agent interactions and analyzing the emergence of creativity in computational systems.