Biological computing using perfusion anodophile biofilm electrodes (PABE)

Greenman, John; Ieropoulos, Ioannis; Melhuish, Chris

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