Nonmodular architectures of cognitive systems based on active inference
arXiv Preprint Archive March 22, 2019 Manuel Baltieri, Christopher L. Buckley
Cognitive systems are often modeled as input/output devices with separate perceptual and motor modules, a view that resonates with the separation principle of control theory. This paper presents a minimal sensorimotor model based on that principle and shows its limitations when external forces—such as environmental perturbations or interference from other agents—are not accounted for. As an alternative, the authors propose a nonmodular architecture grounded in active inference, which demonstrates robustness to unknown external inputs. In linear models, this robustness is achieved through a mechanism equivalent to integral control, offering a principled way to handle disturbances that the agent cannot directly control.