{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T16:44:16Z","timestamp":1778690656743,"version":"3.51.4"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,1,8]],"date-time":"2022-01-08T00:00:00Z","timestamp":1641600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Making computing machines mimic living organisms has captured the imagination of many since the dawn of digital computers. However, today\u2019s artificial intelligence technologies fall short of replicating even the basic autopoietic and cognitive behaviors found in primitive biological systems. According to Charles Darwin, the difference in mind between humans and 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 identity and stability while facing fluctuations caused by external influences. Cognitive behaviors model the system\u2019s state, sense internal and external changes, analyze, predict and take action to mitigate any risk to its functional fulfillment. 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 show how to use the structural machine to build a cognitive reasoning system that integrates the knowledge from various digital symbolic and sub-symbolic computations. This approach is analogous to how the neocortex repurposed the reptilian brain and paves the path for digital machines to mimic living organisms using an integrated knowledge representation from different sources.<\/jats:p>","DOI":"10.3390\/info13010024","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T20:29:26Z","timestamp":1641760166000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A New Class of Autopoietic and Cognitive Machines"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8762-7070","authenticated-orcid":false,"given":"Rao","family":"Mikkilineni","sequence":"first","affiliation":[{"name":"Ageno School of Business, Golden Gate University, San Francisco, CA 94105, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yanai, I., and Martin, L. 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