Artificial cognitive systems: the next generation of the digital twin. An opinion. [version 2; peer review: 2 approved]
The digital twin is often presented as the solution to Industry 4.0 and, while there are many areas where this may be the case, there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability, cause and effec...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2021-11-01
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| Series: | Digital Twin |
| Subjects: | |
| Online Access: | https://digitaltwin1.org/articles/1-3/v2 |
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| Summary: | The digital twin is often presented as the solution to Industry 4.0 and, while there are many areas where this may be the case, there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability, cause and effect, and planning that Industry 4.0 requires. As the limitations of machine learning are beginning to be understood, the paradigm of strong artificial intelligence is emerging. The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world. This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly. This argument is based on the inherent similarities between the digital twin and artificial cognitive systems, and the insights that can already be seen in aligning the two approaches. |
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| ISSN: | 2752-5783 |