Minimizing environmental swings with a recurrent neural network control system

Authors:
Sam Skrivan;Jianna Zhang;Debra Jusak
Affiliations:
Western Washington University, Department of Computer Science;Western Washington University, Department of Computer Science;Western Washington University, Department of Computer Science
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Year:
2005

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Abstract

Maintaining environmental stability in a dynamic system is a difficult challenge. In your living room, when you set your thermostat to 68 degrees the actual temperature cycles above and below 68 degrees. We attempt to use a Recurrent Neural Network (RNN) in an Aquarium Control System that reduces such environmental swings.