Agency Is Frame-Dependent

• DOI: 10.48550/arxiv.2502.04403
• Publication Date: 2025-01-01
• Authors: Abel, David; Barreto, André; Bowling, Michael; Dabney, Will; Dong, Shi; Hansen, Steven; Harutyunyan, Anna; Khetarpal, Khimya; Lyle, Clare; Pascanu, Razvan; Piliouras, Georgios; Precup, Doina; Richens, Jonathan; Rowland, Mark; Schaul, Tom; Singh, Satinder
• Keywords: FOS: Computer and information sciences; Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence

Agency is a system's capacity to steer outcomes toward a goal, and is a central topic of study across biology, philosophy, cognitive science, and artificial intelligence. Determining if a system exhibits agency is a notoriously difficult question: Dennett (1989), for instance, highlights the puzzle of determining which principles can decide whether a rock, a thermostat, or a robot each possess agency. We here address this puzzle from the viewpoint of reinforcement learning by arguing that agency is fundamentally frame-dependent: Any measurement of a system's agency must be made relative to a reference frame. We support this claim by presenting a philosophical argument that each of the essential properties of agency proposed by Barandiaran et al. (2009) and Moreno (2018) are themselves frame-dependent. We conclude that any basic science of agency requires frame-dependence, and discuss the implications of this claim for reinforcement learning.