Active Inference or Control as Inference? A Unifying View

Understand

Active inference (AI) is a persuasive theoretical framework from computational neuroscience that seeks to describe action and perception as inference-based computation.

• However, this framework has yet to provide practical sensorimotor control algorithms that are competitive with alternative approaches.
• In this work, we frame active inference through the lens of control as inference (CaI), a body of work that presents trajectory optimization as inference.
• From the wider view of `probabilistic numerics', CaI offers principled, numerically robust optimal control solvers that provide uncertainty quantification, and can scale to nonlinear problems with approximate inference.