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