发表机构
Université du Québec à Montréal; McMaster University（魁北克大学蒙特利尔分校; 麦克马斯特大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文通过三个机器人艺术装置，探索具身机器学习与数字演化在实时生态中的美学，重新定义艺术家角色，并提出跨学科艺术-科学研究新模式及提升观众体验的策略。
AI 中文摘要
我们展示了三个机器人艺术装置，它们探索了自适应行为的美学。通过具身机器学习和数字演化，这些作品将观众引入一个人工生态系统，在该系统中，开放式新颖性、试错学习、竞争与合作实时涌现。我们结合这些作品审视了研究-创作实践，重点关注它们如何重新定义艺术家在人机集体中的角色，同时考察了艺术与工程方法在自适应机器人学上的趋同与分歧点。所涉系统使用学习和演化过程，并非为了优化特定解决方案，而是将其本身作为一种美学体验，从而提出了跨学科艺术-科学研究的新模式。最后，我们讨论了提升观众美学体验的策略与实践，包括展示语境以及基于具身自适应系统的艺术作品在时间与材料上的考量。
英文摘要
We present three robotic art installations which explore the aesthetics of adaptive behavior. Through embodied machine leaning and digital evolution, these works draw viewers into an artificial ecosystem in which open-ended novelty, trial-and-error learning, competition, and cooperation emerge in real time. Research-creation practices are examined in relation to these works, focusing on how they redefine the role of artists within a human-machine collective while examining points of convergence and divergence between artistic and engineering approaches to adaptive robotics. The systems in question use learning and evolutionary processes not as a means to optimize a specific solution, but as an aesthetic experience on its own, suggesting new modes of interdisciplinary art-science research. Finally, we discuss strategies and practices to elevate the aesthetic experience for audiences, including contexts of presentation as well as temporal and material considerations for artworks based on embodied adaptive systems.
