Preprint Concept Paper Version 1 Preserved in Portico This version is not peer-reviewed

Autopoietic Machines with Structural Information Processing

Version 1 : Received: 23 November 2021 / Approved: 23 November 2021 / Online: 23 November 2021 (10:42:36 CET)

How to cite: Mikkilineni, R.; Burgin, M. Autopoietic Machines with Structural Information Processing. Preprints 2021, 2021110418 (doi: 10.20944/preprints202111.0418.v1). Mikkilineni, R.; Burgin, M. Autopoietic Machines with Structural Information Processing. Preprints 2021, 2021110418 (doi: 10.20944/preprints202111.0418.v1).

Abstract

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.

Keywords

general theory of information; named set; knowledge structure; structural machine; autopoietic machine; multi-cloud infrastructure.

Subject

MATHEMATICS & COMPUTER SCIENCE, Information Technology & Data Management

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