Problem
Research questions and friction points this paper is trying to address.
real-time learning
evolutionary processes
adaptive behavior
artistic experience
human-machine collective
Real-time Learning and Evolution in Robotic Art Installations
🤖 AI Summary
该研究通过机器学习和数字进化在机器人艺术装置中探索适应性行为的美学，创造出实时互动的人工生态系统。
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
embodied machine learning
digital evolution
adaptive robotics
art-science research
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