Behavior Morphologies of Machine Learning Agents in Media Artworks

Abstract

Abstract Since the 1950s, a range of artists have used artificial agents in their work, in parallel with scientific research in cybernetics, artificial intelligence (AI) and artificial life (AL). In particular, an increasing number of artists work with machine learning and other adaptive systems. Through the author's own engagement with such systems, an analysis of adaptive agents is provided within the broader context of behavior aesthetics. As a result, the author proposes an aesthetic framework for understanding behaviors that accounts for the observer as an adaptive perceiving agent, the unfathomable character of machine learning systems and the morphology of behaviors as a time-based phenomenon.