John Greenman john.greenman@uwe.ac.uk
Biological computing using perfusion anodophile biofilm electrodes (PABE)
Greenman, John; Ieropoulos, Ioannis; Melhuish, Chris
Authors
Yannis Ieropoulos Ioannis2.Ieropoulos@uwe.ac.uk
Professor in Bioenergy & Director of B-B
Chris Melhuish Chris.Melhuish@uwe.ac.uk
Professor of Robotics & Autonomous Systems
Abstract
This paper presents a theoretical approach to biological computing, using biofilm electrodes by illustrating a simplified Pavlovian learning model. The theory behind this approach was based on empirical data produced from a prototype version of these units, which illustrated high stability. The implementation of this system into the Pavlovian learning model, is one example and possibly a first step in illustrating, and at the same time discovering its potential as a computing processor. © 2007 Old City Publishing, Inc.
Journal Article Type | Article |
---|---|
Publication Date | Dec 1, 2008 |
Deposit Date | Feb 18, 2013 |
Publicly Available Date | Feb 10, 2016 |
Journal | International Journal of Unconventional Computing |
Print ISSN | 1548-7199 |
Electronic ISSN | 1548-7202 |
Publisher | Old City Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 4 |
Issue | 1 |
Pages | 23-32 |
Keywords | artificial intelligence, biological computing, neurone-like, transistor-like, unit and connected assemblies, Pavlovian association learning |
Public URL | https://uwe-repository.worktribe.com/output/1034959 |
Publisher URL | https://www.oldcitypublishing.com/journals/ijuc-home/ijuc-issue-contents/ijuc-volume-4-number-1-2008/ijuc-4-1-p-23-32/ |
Contract Date | Feb 10, 2016 |
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