Artificial consciousness algorithm for an autonomous system

Author

Johnson, John L. ; Caulfield, H. John ; Taylor, Jaime R.

Author_Institution

V Corps US Army, USA

Volume

5

fYear

2000

fDate

2000

Firstpage

635

Abstract

Conscious behavior is hypothesized to be governed by the dynamics of the neural architecture of the brain. A general model of an artificial consciousness algorithm is presented, and applied to a one-dimensional feedback control system. A new learning algorithm for learning functional relations is presented and shown to be biologically grounded. The consciousness algorithm uses predictive simulation and evaluation to let the example system relearn new internal and external models after it is damaged

Keywords

brain models; feedback; learning (artificial intelligence); neural nets; artificial consciousness algorithm; autonomous system; brain; conscious behavior; example system; external models; functional relations; learning algorithm; neural architecture; one-dimensional feedback control system; predictive simulation; Biological system modeling; Biological systems; Brain modeling; Control systems; Evolution (biology); Feedback control; Physics; Prediction algorithms; Predictive models; Pressing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.861540

Filename

861540