Situational Agency: The Framework for Designing Behavior in Agent-based art
Ary-Yue Huang, Varvara Guljajeva
TL;DR
The paper addresses how to design agent behaviors in artful, interactive systems where meaning emerges from ongoing social and environmental interactions. It introduces situational agency, situating behavior design within the environment as a dynamic semantic network shaped by audience participation and computational systems. By comparing two artwork categories—behavioral evolution through participation and swarm collaboration—the authors develop a framework that guides artists in deploying technologies (e.g., ML, genetic algorithms, NEAT) to craft evolving, lifelike aesthetic experiences. This framework provides practical guidance for practitioners and establishes a theoretical basis for analyzing human–AI co-creative encounters in art and related media.
Abstract
In the context of artificial life art and agent-based art, this paper draws on Simon Penny's {\itshape Aesthetic of Behavior} theory and Sofian Audry's discussions on behavior computation to examine how artists design agent behaviors and the ensuing aesthetic experiences. We advocate for integrating the environment in which agents operate as the context for behavioral design, positing that the environment emerges through continuous interactions among agents, audiences, and other entities, forming an evolving network of meanings generated by these interactions. Artists create contexts by deploying and guiding these computational systems, audience participation, and agent behaviors through artist strategies. This framework is developed by analysing two categories of agent-based artworks, exploring the intersection of computational systems, audience participation, and artistic strategies in creating aesthetic experiences. This paper seeks to provide a contextual foundation and framework for designing agents' behaviors by conducting a comparative study focused on behavioural design strategies by the artists.