Cybernetics, interoception, and the art of embodiment

TL;DR - This work proposes a framework for autonomous embodied agents that combines cybernetics, reinforcement learning, neuroscience and biological interoception. It matters because monitoring internal states alongside the external environment could enable artificial agents to adapt their behavior more autonomously.

• Models biological interoception: organisms’ continuous sensing of internal physiological conditions.
• Integrates internal-state signals with environmental feedback to guide agent actions.
• Connects cybernetic control principles with reinforcement learning and neuroscience.
• Targets more adaptive and autonomous artificial embodied agents.