Theoretical perspectives on active sensing

- Active sensing involves two main processes: perception and action.
- Perception is formalized as an ideal observer and action by an ideal planner.
- Active sensing can be understood as a form of exploration.
- A taxonomy of efficient sensing strategies is developed.
- Many tasks show the hallmarks of active sensing with efficiency often close to optimal.

A key component of interacting with the world is how to direct ones' sensors so as to extract task-relevant information - a process referred to as active sensing. In this review, we present a framework for active sensing that forms a closed loop between an ideal observer, that extracts task-relevant information from a sequence of observations, and an ideal planner which specifies the actions that lead to the most informative observations. We discuss active sensing as an approximation to exploration in the wider framework of reinforcement learning, and conversely, discuss several sensory, perceptual, and motor processes as approximations to active sensing. Based on this framework, we introduce a taxonomy of sensing strategies, identify hallmarks of active sensing, and discuss recent advances in formalizing and quantifying active sensing.