Temporal patterns in artificial reaction networks.

Gerrard, Claire; McCall, John; Coghill, George M.; Macleod, Christopher

Abstract

The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, and S-Systems. This paper discusses the temporal aspects of the ARN model using robotic gaits as an example and compares it with properties of Artificial Neural Networks. The comparison shows that the ARN based network has similar functionality.

Citation

GERRARD, C., MCCALL, J., COGHILL, G.M. and MACLEOD, C. 2012. Temporal patterns in artificial reaction networks. In Villa, A.E.P., Duch, W., Érdi, P., Masulli, F. and Palm, G. (eds.) Artificial neural networks and machine learning: proceedings of the 22nd International conference on artificial neural networks (ICANN 2012), 11-14 September 2012, Lausanne, Switzerland. Lecture notes in computer science, 7552. Berlin: Springer [online], part I, pages 1-8. Available from: https://doi.org/10.1007/978-3-642-33269-2_1

• Conference Name: 22nd International conference on artificial neural networks (ICANN 2012)
• Conference Location: Lausanne, Switzerland
• Start Date: Sep 11, 2012
• End Date: Sep 14, 2012
• Acceptance Date: Sep 30, 2012
• Online Publication Date: Sep 30, 2012
• Publication Date: Sep 30, 2012
• Deposit Date: Sep 26, 2012
• Publicly Available Date: Sep 26, 2012
• Publisher: Springer
• Pages: 1-8
• Series Title: Lecture notes in computer science
• Series Number: 7552
• ISBN: 9783642332654
• DOI: https://doi.org/10.1007/978-3-642-33269-2_1
• Keywords: Artificial neural networks; Artificial reaction networks; Cellular intelligence; Biochemical networks
• Public URL: http://hdl.handle.net/10059/766