Participatory Evolution of Artificial Life Systems via Semantic Feedback

• URL: http://arxiv.org/abs/2507.03839v1
• Date: Fri, 04 Jul 2025 23:51:50 GMT
• Title: Participatory Evolution of Artificial Life Systems via Semantic Feedback
• Authors: Shuowen Li, Kexin Wang, Minglu Fang, Danqi Huang, Ali Asadipour, Haipeng Mi, Yitong Sun,
• Abstract summary: We present a semantic feedback framework that enables natural language to guide the evolution of artificial life systems.<n>The system allows user intent to modulate both visual outcomes and underlying behavioral rules.
• Score: 10.530922022646255
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a semantic feedback framework that enables natural language to guide the evolution of artificial life systems. Integrating a prompt-to-parameter encoder, a CMA-ES optimizer, and CLIP-based evaluation, the system allows user intent to modulate both visual outcomes and underlying behavioral rules. Implemented in an interactive ecosystem simulation, the framework supports prompt refinement, multi-agent interaction, and emergent rule synthesis. User studies show improved semantic alignment over manual tuning and demonstrate the system's potential as a platform for participatory generative design and open-ended evolution.

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