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Building autonomous --- i.e., choosing goals based on one's needs -- andadaptive -- i.e., surviving in ever-changing environments -- agents has been aholy grail of artificial intelligence (AI). A living organism is a primeexample of such an agent, offering important lessons about adaptive autonomy.Here, we focus on interoception, a process of monitoring one's internalenvironment to keep it within certain bounds, which underwrites the survival ofan organism. To develop AI with interoception, we need to factorize the statevariables representing internal environments from external environments andadopt life-inspired mathematical properties of internal environment states.This paper offers a new perspective on how interoception can help buildautonomous and adaptive agents by integrating the legacy of cybernetics withrecent advances in theories of life, reinforcement learning, and neuroscience.

Life-inspired Interoceptive Artificial Intelligence for Autonomous and Adaptive Agents