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Artificial consciousness algorithm for an autonomous system
Resource type
Conference Paper
Authors/contributors
- Johnson, J.L. (Author)
- Caulfield, H.J. (Author)
- TAylor, J.R. (Author)
Title
Artificial consciousness algorithm for an autonomous system
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.
Date
2000
Proceedings Title
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
Conference Name
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
Place
Como, Italy
Publisher
IEEE
Pages
635-640 vol.5
ISBN
978-0-7695-0619-7
Accessed
3/6/25, 4:30 PM
Library Catalog
DOI.org (Crossref)
Citation
Johnson, J. L., Caulfield, H. J., & TAylor, J. R. (2000). Artificial consciousness algorithm for an autonomous system. Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 635–640 vol.5. https://doi.org/10.1109/IJCNN.2000.861540
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