Abstract
It is clear to all, after a moments thought, that nature has much we might be inspired by when designing our systems, for example: robustness, adaptability and complexity, to name a few. The implementation of bio-inspired systems in hardware has however been limited, and more often than not been more a matter of artistry than engineering. The reasons for this are many, but one of the main problems has always been the lack of a universal platform, and of a proper methodology for the implementation of such systems. The ideas presented in this paper are early results of a new research project, “Reconfigurable POEtic Tissue”. The goal of the project is the development of a hardware platform capable of implementing systems inspired by all the three major axes (phylogenesis, ontogenesis, and epigenesis) of bio-inspiration, in digital hardware.
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References
E. Sanchez, D. Mange, M. Sipper, M. Tomassini, A. Perez-Uribe, A. Stauffer. “Phylogeny, Ontogeny, and Epigenesis: Three Sources of Biological Inspiration for Softening Hardware”. Lecture Notes in Computer Science, vol. 1259, Springer-Verlag, Berlin, 1997, pp. 35–54.
M. Mitchell. An Introduction to Genetic Algorithms. MIT Press, Cambridge, MA, 1996.
D.B. Fogel. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE Press, Piscataway, NJ, 1995.
J.R. Koza. Genetic Programming. The MIT Press, Cambridge, MA, 1992.
D. Floreano, J. Urzelai.. “Evolutionary Robots with on-line self-organization and behavioral fitness”. Neural Networks, 13, 431–443.
Krohling, R., Zhou, Y. and Tyrrell, A.M. ‘Evolving FPGA-based robot controllers using an evolutionary algorithm’, 1st International Conference on Artificial Immune Systems, Canterbury, September 2002.
T. Higuchi, M. Iwata, I. Kajitani, M. Murakawa, S. Yoshizawa. “Hardware evolution at gate and function level”. Proc. of Biologically Inspired Autonomous Systems: Computation, Cognition, and Action, Durham, NC, March 1996.
A. Thompson, I. Harvey, and P. Husbands. “Unconstrained evolution and hard consequences”, Towards Evolvable Hardware, Springer, 1996, pp.136–165.
Canham, R.O. and Tyrrell, A.M. ‘Evolved Fault Tolerance in Evolvable Hardware’ Congress on Evolutionary Computation, Hawaii, pp 1267–1272, May 2002.
Roggen, D., Floreano, D., Mattiussi, C. ‘A Morphogenetic System as the Phylogenetic Mechanism of the POEtic Tissue’. Elsewhere in this volume.
C. Ortega, A. Tyrrell, “MUXTREE revisited: Embryonics as a Reconfiguration Strategy in Fault-Tolerant Processor Arrays”, Lecture Notes in Computer Science, Vol. 1478, Springer-Verlag, Berlin, 1998, pp. 206–217.
J. von Neumann. The Theory of Self-Reproducing Automata.A. W. Burks, ed. University of Illinois Press, Urbana, IL, 1966
D. Mange, M. Sipper, A. Stauffer, G. Tempesti. “Towards Robust Integrated Circuits: The Embryonics Approach”. Proceedings of the IEEE, vol. 88, no. 4, April 2000, pp. 516–541.
F. Gruau. “Genetic systems of boolean neural networks with a cell rewriting developmental process”, Combination of Genetic Algorithms and Neural Networks. IEEE Press, Los Alamitos, CA, 1992.
A. Lindenmayer. “Mathematical models for cellular interaction in development, parts I and II”. Journal of Theoretical Biology, 18:280–315, 1968.
H. Kitano. “Building complex systems using developmental process: An engineering approach”, Lecture Notes in Computer Science, vol. 1478, Springer-Verlag, Berlin, 1998. pp. 218–229.
G Tempesti, D. Roggen, E Sanchez, Y Thoma, R. Canham, A.M. Tyrrell. ‘Ontogrnetic Development and Fault Tolerance in the POEtic Tissue’, Elsewhere in this volume.
P.H. Winston. Artificial Intelligence. Addison-Wesley, Reading, MA, 3rd edition, 1992.
Maass, W and Bishop C.M. “Pulsed Neural Networks”, MIT Press, 1999.
Fusi, S. “Long term memory: Encoding and storing strategies of the brain”, Neurocomputing, 38-40, 1223–1228.
Eriksson, J., Torres, O., Mitchell, A., Tucker, G., Lindsay, K., Halliday, D., Rosenberg, J., Moreno, J., Villa, A. ‘Spiking Neural Networks for Reconfigurable POEtic Tissue’. Elsewhere in this volume.
Bradley, D.W. and Tyrrell, A.M. ‘Immunotronics: Novel Finite State Machine Architectures with Built in Self Test using Self-Nonself Differentiation’, IEEE Transactions on Evolutionary Computation, Vol 6, No 3, pp 227–238, June 2002.
Urzelai, J. and Floreano, D. (2001) Evolution of Adaptive Synapses: Robots with Fast Adaptive Behavior in New Environments. Evolutionary Computation, 9, 495–524.
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Tyrrell, A.M. et al. (2003). POEtic Tissue: An Integrated Architecture for Bio-inspired Hardware. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds) Evolvable Systems: From Biology to Hardware. ICES 2003. Lecture Notes in Computer Science, vol 2606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36553-2_12
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DOI: https://doi.org/10.1007/3-540-36553-2_12
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