Browse Publications Technical Papers 2004-01-2440

Reinforcement Learning in the Control of a Simulated Life Support System 2004-01-2440

To make extended space missions, such as missions to Mars, a reality, an advanced life support system (ALS) must be developed that is able to utilize resources to their fullest capabilities [2]. In order to make such a system a reality, a robust control system must be developed that is able to cope with the complexity of an ALS.
This work applies reinforcement learning (RL), a machine learning technique, to the task of controlling the water recovery system of a simulated ALS. The RL agent learns an effective control strategy that extends the mission length to the point that lack of water is no longer the cause of mission termination.


Subscribers can view annotate, and download all of SAE's content. Learn More »


Members save up to 43% off list price.
Login to see discount.
Special Offer: With TechSelect, you decide what SAE Technical Papers you need, when you need them, and how much you want to pay.