基于智能体的泰山文化IP设计研究
Research on the Design of Mount Tai Cultural IP Based on AI Agents
DOI: 10.12677/jc.2026.148210, PDF,    科研立项经费支持
作者: 刘子兴, 孔 权, 游小满:武汉工程大学艺术设计学院,湖北 武汉
关键词: 智能体(AI Agent)泰山文化文化IP数字创意智能设计AI Agent Mount Tai Culture Cultural IP Digital Creativity Intelligent Design
摘要: 随着人工智能技术的快速发展,AI智能体(Artificial Intelligent Agent,即AI Agent)逐渐成为数字内容创作的重要工具,也为传统文化的创新传播提供了新的技术路径。泰山文化作为中华优秀传统文化的重要组成部分,具有丰富的历史内涵、文化符号和艺术价值,但在传统文化知识产权(Intellectual Property,即IP)设计过程中仍存在资料整理效率低、文化元素提炼困难、设计周期长以及创意表达不足等问题。针对上述问题,本文以“岱宗文枢·泰山文化智创平台”为实践对象,基于Minimax智能体平台构建文化创意设计流程,并调用火山引擎语言大模型、文生图模型及图生图模型,实现泰山文化资料整理、设计方案生成、视觉形象创作及优化等功能。通过对平台设计流程和IP设计实践的分析,验证了AI智能体在文化资源整合、创意辅助和视觉设计等方面的应用价值。研究表明,AI智能体能够提升泰山文化IP设计效率,增强文化元素表达的完整性和一致性,为地方文化数字化传播和文化创意产品开发提供了新的设计思路和实践参考。
Abstract: With the rapid development of artificial intelligence technology, AI agents have gradually become vital tools for digital content creation, offering new technical pathways for the innovative dissemination of traditional culture. As a significant component of China’s excellent traditional culture, Mount Tai culture possesses rich historical connotations, cultural symbols, and artistic value; however, the design process for its cultural intellectual property (IP) faces challenges such as inefficient data organization, difficulties in distilling cultural elements, lengthy design cycles, and inadequate creative expression. To address these issues, this paper focuses on the “Daizong Wenshu: Mount Tai Cultural Intelligent Creation Platform” as a case study. It establishes a cultural creative design workflow based on the Minimax AI agent platform and integrates Volcengine’s large language models, text-to-image models, and image-to-image models to facilitate functions such as organizing Mount Tai cultural data, generating design proposals, and creating and optimizing visual imagery. An analysis of the platform’s design workflow and IP design practices validates the value of AI agents in cultural resource integration, creative assistance, and visual design. The study demonstrates that AI agents can enhance the efficiency of Mount Tai cultural IP design and improve the integrity and consistency of cultural element expression, thereby providing new design approaches and practical references for the digital dissemination of local culture and the development of cultural creative products.
文章引用:刘子兴, 孔权, 游小满. 基于智能体的泰山文化IP设计研究[J]. 新闻传播科学, 2026, 14(8): 125-131. https://doi.org/10.12677/jc.2026.148210

参考文献

[1] 王青原, 白贵. 中华优秀传统文化数字化传承与出版创新: IP转化与国际传播的双轮驱动[J]. 中州学刊, 2025(9): 170-176.
[2] Zhou, J., Li, R., Tang, J., Tang, T., Li, H., Cui, W., et al. (2024) Understanding Nonlinear Collaboration between Human and AI Agents: A Co-Design Framework for Creative Design. Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu, 11-16 May 2024, 1-16.
https://doi.org/10.1145/3613904.3642812
[3] 许为. 九论以用户为中心的设计: 智能时代的“用户体验3.0”范式[J]. 应用心理学, 2024, 30(2): 99-117.
[4] Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., et al. (2024) A Survey on Large Language Model Based Autonomous Agents. Frontiers of Computer Science, 18, Article No. 186345.
https://doi.org/10.1007/s11704-024-40231-1
[5] Lewis, P., et al. (2020) Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. Proceedings of the 34th International Conference on Neural Information Processing Systems, Vancouver, 6-12 December 2020, 9459-9474.
[6] Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., et al. (2022) Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Advances in Neural Information Processing Systems 35, New Orleans, 28 November-9 December 2022, 24824-24837.
https://doi.org/10.52202/068431-1800
[7] Wu, T., Jiang, E., Donsbach, A., Gray, J., Molina, A., Terry, M., et al. (2022) PromptChainer: Chaining Large Language Model Prompts through Visual Programming. CHI Conference on Human Factors in Computing Systems Extended Abstracts, New Orleans, 29 April-5 May 2022, 1-10.
https://doi.org/10.1145/3491101.3519729
[8] Zhang, W., Zhang, J., Wong, K., Wang, Y., Feng, Y., Wang, L., et al. (2024) Computational Approaches for Traditional Chinese Painting: From the “Six Principles of Painting” Perspective. Journal of Computer Science and Technology, 39, 269-285.
https://doi.org/10.1007/s11390-024-3408-x
[9] 张婧雅, 张玉钧. 自然保护地的文化景观价值演变与识别——以泰山为例[J]. 自然资源学报, 2019, 34(9): 1833-1849.