Temporal Patterns in Artificial Reaction Networks

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.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  Toshiyuki Nakagaki,et al.  Amoebae anticipate periodic events. , 2008, Physical review letters.

[3]  T. Nakagaki,et al.  Intelligence: Maze-solving by an amoeboid organism , 2000, Nature.

[4]  George M. Coghill,et al.  Artificial reaction networks , 2011 .

[5]  P. B. Chock,et al.  Interconvertible enzyme cascades in metabolic regulation. , 1978, Current topics in cellular regulation.

[6]  A. Hjelmfelt,et al.  Mass-coupled chemical systems with computational properties , 1993 .

[7]  J. J. Collins,et al.  Hard-wired central pattern generators for quadrupedal locomotion , 1994, Biological Cybernetics.

[8]  A. Dagg.  Gaits in mammals , 1973 .

[9]  Marta Simeoni,et al.  Petri nets for modelling metabolic pathways: a survey , 2010, Natural Computing.

[10]  Baojun Wang,et al.  Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology , 2011, Nature communications.

[11]  Aude Billard,et al.  Biologically inspired neural controllers for motor control in a quadruped robot , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[12]  J. Ross,et al.  Computational functions in biochemical reaction networks. , 1994, Biophysical journal.

[13]  Upinder S Bhalla,et al.  Understanding complex signaling networks through models and metaphors. , 2003, Progress in biophysics and molecular biology.

[14]  D. Bray.  Protein molecules as computational elements in living cells , 1995, Nature.

[15]  M. Hildebrand.  Analysis of Asymmetrical Gaits , 1977 .

[16]  Christopher MacLeod,et al.  Incremental growth in modular neural networks , 2009, Eng. Appl. Artif. Intell..

[17]  B. Kholodenko.  Cell-signalling dynamics in time and space , 2006, Nature Reviews Molecular Cell Biology.

[18]  T. Helikar,et al.  Emergent decision-making in biological signal transduction networks , 2008, Proceedings of the National Academy of Sciences.

[19]  Z. Afelt,et al.  Speed control in animal locomotion: transitions between symmetrical and nonsymmetrical gaits in the dog. , 1983, Acta neurobiologiae experimentalis.

[20]  E. Voit,et al.  Recasting nonlinear differential equations as S-systems: a canonical nonlinear form , 1987 .