Reinforcement Learning in the Control of a Simulated Life Support System Department of Computer Science, TexasTechUniversity

Format:

Conference/Event

Author/Creator:

Quasny, Todd M., author.

Conference Name:

International Conference On Environmental Systems (2004-07-19 : Colorado Springs, Colorado, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2004

Summary:

AbstractTo 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

Notes:

Vendor supplied data

Publisher Number:

2004-01-2440

Access Restriction:

Restricted for use by site license