An Advanced Life Support System (ALS) recycles and circulates materials within a living environment, and will eventually make it possible to sustain life in outer space. This study addresses the system subset that will recycle the elements of carbon, hydrogen and oxygen, with planned functions that include waste recycling and food production. We have previously proposed a procedure for such a system that combines automatic generation of scheduling and multi-agent reinforcement learning (MARL), based on a hierarchical control method. This paper reports the application of this procedure during a material circulation simulation that includes modifications to the system. Specifically, a waste processor was added in the midst of the simulation during its calculations. As the simulation continued, an initial issue with over-operation of the waste processor under the decentralized autonomous system developed, but this was resolved by the hierarchical control procedure. The calculation results confirmed that no disturbances occurred in the scheduling-based upper control layer after the increase in waste processors. The lower control system, exercising decentralized autonomous control, functioned to follow current conditions in the new environment.Nomenclature CO 2 Risk = risk level at CO 2 tank O 2 Risk = risk level at O 2 tank penalty = the weighting determining how much the activation probability should be reduced due to process interruption Rule [i][j] = he activation probability during condition i, . w = the assessment weighting for determining the amount of change