Issues in the Scalability of Gate-level Morphogenetic Evolvable Hardware
Lee, Justin & Sitte, Joaquin (2005) Issues in the Scalability of Gate-level Morphogenetic Evolvable Hardware. In Abbass, H.A., Bossamaier, T., & Wiles, J. (Eds.) Recent Advances in Artificial Life. World Scientific, pp. 145-158.
Traditional approaches to evolvable hardware (EHW), in which the field programmable gate array (FPGA) configuration is directly encoded, have not scaled well with increasing circuit and FPGA complexity. To overcome this there have been moves towards encoding a growth process, known as morphogenesis. Using a morphogenetic approach, has shown success in scaling gate-level EHW for a signal routing problem, however, when faced with a evolving a one-bit full adder, unforseen difficulties were encountered.
In this paper, we provide a measurement of EHW problem difficulty that takes into account the salient features of the problem, and when combined with a measure of feedback from the fitness function, we are able to estimate whether or not a given EHW problem is likely to be able to be solved successfully by our morphogenetic approach. Using these measurements we are also able to give an indication of the scalability of morphogenesis when applied to EHW.
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|Item Type:||Book Chapter|
|Additional Information:||This is the author’s manuscript version of the work. It is posted here with permission of the copyright owner for your personal use only. No further distribution is permitted. For more information about this book please refer to the publisher's website (see link) or contact the author. Author contact details: email@example.com|
|Keywords:||Evolvable Hardware, Morphogenesis, Field Programmable Gate Arrays, Scalability|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Electrical and Electronic Engineering not elsewhere classified (090699)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2005 World Scientific|
|Deposited On:||13 Dec 2005 00:00|
|Last Modified:||29 Feb 2012 13:13|
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