A novel way to model an agent interacting with an environment is introduced, called an
Enactive Markov Decision Process (EMDP). An EMDP keeps perception and action
embedded within sensorimotor schemes rather than dissociated, in compliance with
theories of embodied cognition. Rather than seeking a goal associated with a reward, as in
reinforcement learning, an EMDP agent learns to master the sensorimotor contingencies
offered by its coupling with the environment. In doing so, the agent exhibits a form of intrinsic …