Evolvable Hardware Challenges: Past, Present and the Path to a Promising Future

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{Haddow:2017:miller,

• author = "Pauline C. Haddow and Andy M. Tyrrell",
• title = "Evolvable Hardware Challenges: Past, Present and the Path to a Promising Future",
• booktitle = "Inspired by Nature: Essays Presented to Julian F. Miller on the Occasion of his 60th Birthday",
• publisher = "Springer",
• year = "2017",
• editor = "Susan Stepney and Andrew Adamatzky",
• volume = "28",
• series = "Emergence, Complexity and Computation",
• chapter = "1",
• pages = "3--37",
• keywords = "genetic algorithms, genetic programming, EHW",
• isbn13 = "978-3-319-67996-9",
• DOI = "doi:10.1007/978-3-319-67997-6_1",
• abstract = "The ability of the processes in Nature to achieve remarkable examples of complexity, resilience, inventive solutions and beauty is phenomenal. This ability has promoted engineers and scientists to look to Nature for inspiration. Evolvable Hardware (EH) is one such form of inspiration. It is a field of evolutionary computation (EC) that focuses on the embodiment of evolution in a physical media. If EH could achieve even a small step in natural evolution's achievements, it would be a significant step for hardware designers. Before the field of EH began, EC had already shown artificial evolution to be a highly competitive problem solver. EH thus started off as a new and exciting field with much promise. It seemed only a matter of time before researchers would find ways to convert such techniques into hardware problem solvers and further refine the techniques to achieve systems that were competitive (better) than human designs. However, almost 20 years on, it appears that problems solved by EH are only of the size and complexity of that achievable in EC 20 years ago and seldom compete with traditional designs. A critical review of the field is presented. Whilst highlighting some of the successes, it also considers why the field is far from reaching these goals. The chapter further redefines the field and speculates where the field should go in the next 10 years.",
• notes = "part of \cite{miller60book} https://link.springer.com/bookseries/10624",

}

Genetic Programming entries for Pauline Haddow Andrew M Tyrrell

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