Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A New Class of Autopoietic and Cognitive Machines

Version 1 : Received: 18 November 2021 / Approved: 19 November 2021 / Online: 19 November 2021 (08:16:17 CET)

A peer-reviewed article of this Preprint also exists.

Mikkilineni, R. A New Class of Autopoietic and Cognitive Machines. Information 2022, 13, 24. Mikkilineni, R. A New Class of Autopoietic and Cognitive Machines. Information 2022, 13, 24.


Making computing machines mimic living organisms has captured the imagination of many since the dawn of digital computers. However, today’s artificial intelligence technologies fall short in replicating even the basic autopoietic and cognitive behaviors found in primitive biological systems. According Charles Darwin, the difference in mind between humans and the higher animals, great as it is, certainly is one of degree and not of kind. Autopoiesis refers to the behavior of a system that replicates itself and maintains its own identity and stability while facing fluctuations caused by external influences. Cognitive behaviors model the system’s state, sense internal and external changes, analyze, predict and take action to mitigate any risk to its functional fulfilment. How did intelligence evolve? what is the relationship between the mind and body? Answers to these questions should guide us to infuse autopoietic and cognitive behaviors into digital machines. In this paper we use recent advances in our understanding of general theory of information, and the role of structures in managing the transformations between information and knowledge to pave the path to infuse autopoietic and cognitive functions into digital computing and build a new class of intelligent machines going beyond the current state of the art.


Cognition; computing models; Deep Learning; Autopoiesis; Structural Machines; Artificial Intelligence


Computer Science and Mathematics, Artificial Intelligence and Machine Learning

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0

Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.