Artificial nervous systems - A technology to achieve biologically modeled intelligence and control for robotics

Fredric Narcross

Research output: Contribution to journalConference articlepeer-review


Migrating from machine learning and deep learning into the next wave of technology will likely require biological replication rather than biological inspiration. An approach to achieving this requires duplicating entire nervous systems, or at least parts thereof. In theory, these artificial nervous systems (ANS) could reproduce everything required for a system to be biologically intelligent even to the point of being self-aware. This would additionally entail that the resultant systems have the ability to acquire information from both their internal and external environments as well as having the ability to act within the external environment using locomotion and manipulators. Robots are a natural answer for the resultant mechanism and if supplied with an artificial nervous system, the robot might be expected to achieve biologically modelled intelligence (BMI) and control. This paper will provide an overview of the tools for creating artificial nervous systems, as well as provide a roadmap for utilizing the tools to develop robots with general-purpose learning skills and biologically modelled intelligence.

Original languageEnglish
Article number012008
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - 1 Jan 2023
Event2022 International Joint Conference on Robotics and Artificial Intelligence, JCRAI 2022 - Virtual, Online
Duration: 14 Oct 202217 Oct 2022

ASJC Scopus subject areas

  • General Physics and Astronomy


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