英語/生物「A Field Guide to Genetic Programming/遺伝子プログラミングへのフィールドガイド」Riccardo Poli, William B. Langdon, Nicholas F. McPhee共著, John R. Koza寄稿 Lulu Enterprises Uk Ltd 2008年3月発行 235頁 22.9×15.3×1.7㎝ 0.4㎏ Paperback
【内容紹介】Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.
【ウィキペディア他より著者紹介】・Riccardo Poli (born 1961) is a Professor in the Department of Computing and Electronic Systems of the University of Essex. His work has centered on genetic programming.……
・William B. Langdon is a professorial research fellow with UCL. He worked on distributed real time databases for control and monitoring of power stations in the Central Electricity Research Laboratories. He then joined Logica to work on distributed control of gas pipelines and later on computer and telecommunications networks. After returning to academia to gain a PhD in GP at UCL, he worked with the University of Birmingham, the CWI, UCL, Essex University, King’s College, London and now for a third time at UCL. (Based on document published on 29 June 2017).
・Nicholas F. McPhee Professor at University of Minnesota, Morris. I teach a broad range of computer science and interdisciplinary courses. This includes key software design and development courses, systems courses, a variety of upper level electives (mostly on artificial intelligence, machine learning, and software development topics), and introductory courses. I have also taught interdisciplinary courses on topics such as American roots music, climate change, open source and network economics, and ethical and social implications of technology.……
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