Cell Assembly-based Task Analysis (CAbTA)

Diaper, Dan and Huyck, Christian R. ORCID: https://orcid.org/0000-0003-4015-3549 (2021) Cell Assembly-based Task Analysis (CAbTA). Arai, Kohei, ed. Intelligent Computing: Proceedings of the 2021 Computing Conference, Volume 1. In: Computing Conference 2021 (formerly called Science and Information (SAI) Conference), 15-16 July 2021, Virtual (from London, UK). ISBN 9783030801182, e-ISBN 9783030801199. ISSN 2367-3370 [Conference or Workshop Item] (doi:10.1007/978-3-030-80119-9_22)

Preview

PDF - Final accepted version (with author's formatting)
Download (1MB) | Preview

Official URL: https://doi.org/10.1007/978-3-030-80119-9_22

Abstract

Based on an Artificial Neural Network model, Cell Assembly-based Task Analysis is a new method that outputs a task performance model composed of integrated mind-brain Cell Assemblies, which are currently believed to be the most plausible, general organisation of the brain and how it supports mental operations. A simplified model of Cell Assemblies and their cognitive architecture is described and then used in the method. A brief sub-task is analysed. The method’s utility to research in Artificial Intelligence, neuroscience and cognitive psychology is discussed and the possibility of a General Theory suggested.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Published as: Diaper D., Huyck C. (2022) Cell Assembly-based Task Analysis (CAbTA). In: Arai K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-030-80119-9_22
Research Areas:	A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID:	33474
Notes on copyright:	© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Useful Links:	Publisher's T&Cs Publisher's T&Cs Event Data or Supplementary Material Publication Publisher Middlesex University Expert Profile
Depositing User:	Chris Huyck
Date Deposited:	02 Jul 2021 17:52
Last Modified:	29 Nov 2022 17:48
URI:	https://eprints.mdx.ac.uk/id/eprint/33474

Actions (login required)

View Item

Statistics

DownloadsShow export options

Activity Overview

6 month trend

40Downloads

6 month trend

108Hits

Additional statistics are available via IRStats2.

CORE (COnnecting REpositories)