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ICCC 2026: International Conference on Computational Creativity

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截稿日期:
2026-03-01 Extended
通知日期:
2026-04-20
会议日期:
2026-06-29
会议地点:
Coimbra, Portugal
届数:
17
ICORE: C   浏览: 905   关注: 0   参加: 0

会伴指数 (CP-I)

52.8 / 100
全站第 1,099 名 / 共 5,687 个会议 · 前 20%
学术认可 (35%)
58
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
78
社区关注 (10%)
16
资料公开度 (15%)
35

用到的输入: 收录等级：ICORE C · 有据可查的届次：17 · 过去 24 个月打开过本页的研究者：8 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-29

征稿

ICCC 2026 (International Conference on Computational Creativity) is a ICORE C conference held in Coimbra, Portugal on 2026-06-29. The paper submission deadline is 2026-03-01 (extended). Acceptance notifications are sent on 2026-04-20.

Themes and Topics Original research contributions are solicited in all areas related to Computational Creativity research and practice, including, but not limited to: Foundations of Computational Creativity: theories, models, and principles of computational creativity. Interdisciplinary Perspectives: perspectives on computational creativity which draw from philosophical and/or sociological studies in the context of creative AI systems. Computational Paradigms: computational approaches for modelling cognitive aspects of creativity, such as heuristic search, analogical and meta-level reasoning, cognitive architectures, and re-representation. Human-Machine Co-Creativity: systems, studies, frameworks, or methodologies related to co-creativity between humans and AI, with emphasis on systems in which the machine acts as a creative partner. Social Models: computational models of social aspects of creativity, including: social creativity, the diffusion of ideas, collaboration, team dynamics, and creativity in social settings. Psychological Factors: computational models of psychological factors that enhance creativity, including emotion, surprise (unexpectedness), reflection, conflict, diversity, motivation, knowledge, intuition, reward structures. Additionally, social or experiential factors related to novelty and originality, such as innovation, improvisation, and virtuosity. Societal Impact: ethical considerations in the design, deployment or testing of creative AI systems, as well as studies that explore the societal impact of computational creativity and generative AI. Computational Creativity Evaluation: metrics, frameworks, formalisms and methodologies for the evaluation of creativity in computational systems, or for the evaluation of how such systems are perceived/accepted in society. Applications of Computational Creativity: computational applications of creativity in areas such as music, language (e.g, narrative, poetry, humor), games, visual arts, design, architecture, entertainment, education, mathematical invention, scientific discovery, programming. Applications should be evaluated for their creativity using methods of the CC field, and the papers should carry a message relevant for the CC community. Data and Creativity: data science approaches to computational creativity: resource development and data gathering/knowledge curation for creative AI. There is a need for datasets and resources that are scalable, extensible and freely available/open-source. Provocations: raising new issues not on this list that bring the foundations of the discipline into question or throw new light on seemingly settled debates. A note on generative AI models: while the study of generative AI models is both welcomed and encouraged, such models and their application must be properly situated in the CC literature and evaluated according to acceptable practices in the field. Papers that fail to do this are unlikely to be reviewed favorably.
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