how to implement a custom environment with continuous state and action spaces in the reinforcement learning framework under Julia? for example, to control the attitude of satellite we need the definition of: (i) markovian state as 7 dimensional real vector(4 for quaternion and 3 for angular rate), and (ii) the 3D action space as it is a 3-axis stabilisation problem.
1 Like