  Time Slotted Channel Hopping (TSCH) behavioural mode has been introduced in
IEEE 802.15.4e standard to address the ultra-high reliability and ultra-low
power communication requirements of Industrial Internet of Things (IIoT)
networks. Scheduling the packet transmissions in IIoT networks is a difficult
task owing to the limited resources and dynamic topology. In this paper, we
propose a phasic policy gradient (PPG) based TSCH schedule learning algorithm.
The proposed PPG based scheduling algorithm overcomes the drawbacks of totally
distributed and totally centralized deep reinforcement learning-based
scheduling algorithms by employing the actor-critic policy gradient method that
learns the scheduling algorithm in two phases, namely policy phase and
auxiliary phase.
