Abstract
Evolvable Hardware (EHW) has been proposed as a new method for designing electronic circuits. In this paper it is applied for evolving a prosthetic hand controller. The novel controller architecture is based on digital logic gates. A set of new methods to incrementally evolve the system is described. This includes several different variants of the fitness function being used. By applying the proposed schemes, the generalisation of the system is improved.
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References
R.N. Scott and P.A. Parker. Myoelectric prostheses: State of the art. J. Med. Eng. Technol., 12:143–151, 1988.
S. Fuji. Development of prosthetic hand using adaptable control method for human characteristics. In Proc. of Fifth International Conference on Intelligent Autonomous Systems., pages 360–367, 1998.
I. Kajitani and other. An evolvable hardware chip and its application as a multifunction prosthetic hand controller. In Proc. of 16th National Conference on Artificial Intelligence (AAAI-99), 1999.
W-P. Lee et al. Learning complex robot behaviours by evolutionary computing with task decomposition. In Andreas Brink and John Demiris, editors, Learning Robots: Proc. of 6th European Workshop, EWLR-6 Brighton. Springer, 1997.
X. Yao and T. Higuchi. Promises and challenges of evolvable hardware. In T. Higuchi et al., editors, Evolvable Systems: From Biology to Hardware. First Int. Conf., ICES 96. Springer-Verlag, 1997. Lecture Notes in Computer Science, vol. 1259.
J. Torresen. Scalable evolvable hardware applied to road image recognition. In Proc. of the 2nd NASA/DoD Workshop on Evolvable Hardware. Silicon Valley, USA, July 2000.
J. Torresen. A divide-and-conquer approach to evolvable hardware. In Evolvable Systems: From Biology to Hardware. Second Int. Conf., ICES 98, pages 57–65. Springer-Verlag, 1998. Lecture Notes in Computer Science, vol. 1478.
J. Torresen. Two-step incremental evolution of a digital logic gate based prosthetic hand controller. In Evolvable Systems: From Biology to Hardware. Fourth Int. Conf., ICES’01). Springer-Verlag, 2001. Lecture Notes in Computer Science, vol. 2210.
M. Yasunaga et al. Genetic algorithm-based design methodology for pattern recognition hardware. In J. Miller et al., editors, Evolvable Systems: From Biology to Hardware. Third Int. Conf., ICES 2000. Springer-Verlag, 2000. Lecture Notes in Computer Science, vol. 1801.
D. Goldberg. Genetic Algorithms in search, optimization, and machine learning. Addison Wesley, 1989.
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Torresen, J. (2002). A Dynamic Fitness Function Applied to Improve the Generalisation when Evolving a Signal Processing Hardware Architecture. In: Cagnoni, S., Gottlieb, J., Hart, E., Middendorf, M., Raidl, G.R. (eds) Applications of Evolutionary Computing. EvoWorkshops 2002. Lecture Notes in Computer Science, vol 2279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46004-7_27
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DOI: https://doi.org/10.1007/3-540-46004-7_27
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