Creative Agents: Simulating the Systems Model of Creativity with Generative Agents
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866915484866183168 |
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| author | Imasato, Naomi Miyazawa, Kazuki Nagai, Takayuki Horii, Takato |
| author_facet | Imasato, Naomi Miyazawa, Kazuki Nagai, Takayuki Horii, Takato |
| contents | With the growing popularity of generative AI for images, video, and music, we witnessed models rapidly improve in quality and performance. However, not much attention is paid towards enabling AI's ability to "be creative". In this study, we implemented and simulated the systems model of creativity (proposed by Csikszentmihalyi) using virtual agents utilizing large language models (LLMs) and text prompts. For comparison, the simulations were conducted with the "virtual artists" being: 1)isolated and 2)placed in a multi-agent system. Both scenarios were compared by analyzing the variations and overall "creativity" in the generated artifacts (measured via a user study and LLM). Our results suggest that the generative agents may perform better in the framework of the systems model of creativity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_17065 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Creative Agents: Simulating the Systems Model of Creativity with Generative Agents Imasato, Naomi Miyazawa, Kazuki Nagai, Takayuki Horii, Takato Multiagent Systems Artificial Intelligence With the growing popularity of generative AI for images, video, and music, we witnessed models rapidly improve in quality and performance. However, not much attention is paid towards enabling AI's ability to "be creative". In this study, we implemented and simulated the systems model of creativity (proposed by Csikszentmihalyi) using virtual agents utilizing large language models (LLMs) and text prompts. For comparison, the simulations were conducted with the "virtual artists" being: 1)isolated and 2)placed in a multi-agent system. Both scenarios were compared by analyzing the variations and overall "creativity" in the generated artifacts (measured via a user study and LLM). Our results suggest that the generative agents may perform better in the framework of the systems model of creativity. |
| title | Creative Agents: Simulating the Systems Model of Creativity with Generative Agents |
| topic | Multiagent Systems Artificial Intelligence |
| url | https://arxiv.org/abs/2411.17065 |