Active Inference in Robotics and Artificial Agents: Survey and Challenges

Understand

Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning.

• Recently, it has been shown to be a promising approach to the problems of state-estimation and control under uncertainty, as well as a foundation for the construction of goal-driven behaviours in robotics and artificial agents in general.
• Here, we review the state-of-the-art theory and implementations of active inference for state-estimation, control, planning and learning; describing current achievements with a particular focus on robotics.
• We showcase relevant experiments that illustrate its potential in terms of adaptation, generalization and robustness.