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Proceeding Paper

Designing New Forms of Digital Autopoietic Machines †

1
Ageno School of Business, Golden Gate University, San Francisco, CA 94105, USA
2
Mathematics Department, University of California, Los Angeles, CA 90095, USA
*
Author to whom correspondence should be addressed.
Presented at the Conference on Theoretical and Foundational Problems in Information Studies, IS4SI Summit 2021, online, 12–19 September 2021.
Academic Editor: H. Paul Zellweger
Proceedings 2022, 81(1), 59; https://doi.org/10.3390/proceedings2022081059
Published: 21 March 2022
The general theory of information (GTI) tells us that information is represented, processed and communicated using physical structures. The physical universe is made up of structures combining matter and energy. According to GTI, “information is related to knowledge as energy is related to matter.” GTI also provides tools to deal with transformation of information and knowledge. We present here the application of these tools for the design of digital autopoietic machines with higher efficiency, resiliency and scalability than the information processing systems based on the Turing machines. We discuss the utilization of these machines for building autopoietic and cognitive applications in a multi-cloud infrastructure. View Full-Text
Keywords: general theory of information; named set; knowledge structure; structural machine; autopoietic machine; multi-cloud infrastructure general theory of information; named set; knowledge structure; structural machine; autopoietic machine; multi-cloud infrastructure
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MDPI and ACS Style

Mikkilineni, R.; Burgin, M. Designing New Forms of Digital Autopoietic Machines. Proceedings 2022, 81, 59. https://doi.org/10.3390/proceedings2022081059

AMA Style

Mikkilineni R, Burgin M. Designing New Forms of Digital Autopoietic Machines. Proceedings. 2022; 81(1):59. https://doi.org/10.3390/proceedings2022081059

Chicago/Turabian Style

Mikkilineni, Rao, and Mark Burgin. 2022. "Designing New Forms of Digital Autopoietic Machines" Proceedings 81, no. 1: 59. https://doi.org/10.3390/proceedings2022081059

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