Why Greatness Cannot Be Planned - nouveau livre

Livre dans la base de données depuis 2015-06-24T12:25:40+02:00 (Paris)
Page de détail modifiée en dernier sur 2023-03-26T00:26:41+01:00 (Paris)
ISBN/EAN: 9783319155241

ISBN - Autres types d'écriture:
3-319-15524-5, 978-3-319-15524-1
Autres types d'écriture et termes associés:
Auteur du livre: lehman, stanley
Titre du livre: objective

Données de l'éditeur

Auteur: Kenneth O. Stanley; Joel Lehman
Titre: Why Greatness Cannot Be Planned - The Myth of the Objective
Editeur: Springer; Springer International Publishing
141 Pages
Date de parution: 2015-05-05
Cham; CH
Imprimé / Fabriqué en
Langue: Anglais
32,09 € (DE)
33,00 € (AT)
35,50 CHF (CH)
Available
IX, 141 p. 14 illus., 5 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Achievement; artificial intelligence (AI); creativity; deception; discovery; education; evolution; evolutionary computation (EC); innovation; machine learing; novelty; objectives; search; serendipity; B; Artificial Intelligence; Artificial Intelligence; Computer Science; BC

, Stanley and Lehman begin with a surprising scientific discovery in artificial intelligence that leads ultimately to the conclusion that the objective obsession has gone too far. They make the case that great achievement can't be bottled up into mechanical metrics; that innovation is not driven by narrowly focused heroic effort; and that we would be wiser (and the outcomes better) if instead we whole-heartedly embraced serendipitous discovery and playful creativity.

Controversial at its heart, yet refreshingly provocative, this book challenges readers to consider life without a destination and discovery without a compass.

Questioning Objectives.-Victory for the Aimless.- The Art of Breeding Art.- The False Compass.- The Interesting and the Novel.- Long Live the Treasure Hunter.- Unshackling Education.- Unchaining Innovation.- Farewell to the Mirage.- Case Study 1: Reinterpreting Natural Evolution.- Case Study 2: Objectives and the Quest for AI.

“It is a very nicely written and enjoyable book, aimed at a general readership. It is also surely worthwhile reading for Artificial Intelligence (AI) researchers, particularly for those of us working in genetic programming. … I recommend Why Greatness Cannot be Planned. It is definitely unique within the evolutionary computation community.” (Leonardo Trujillo, Genetic Programming and Evolvable Machines, Vol. 16, 2015)

Kenneth O. Stanley and coauthor Joel Lehman are both experienced artificial intelligence researchers whose scientific discoveries led to the insights in "Why Greatness Cannot Be Planned." Stanley, an associate professor at the University of Central Florida, has published over 80 peer-reviewed articles (10 of which have won best paper awards) and is regularly invited to speak at venues across the world.  Lehman is currently a post-doctoral fellow at the University of Texas at Austin. In August 2015 he begins as an assistant professor at the IT University of Copenhagen.

     - Christos Papadimitriou, C. Lester Hogan Professor of Computer Science, University of California, Berkeley and Co-author of the New York Times Best Seller “Logicomix”

       - Josh Bongard, Associate Professor of Computer Science, University of Vermont

       - Andrea Soltoggio, Lecturer in Computer Science, Loughborough University, UK

Kenneth O. Stanley and coauthor Joel Lehman are both experienced artificial intelligence researchers whose scientific discoveries led to the insights in “Why Greatness Cannot Be Planned.” Stanley, an associate professor at the University of Central Florida, has published over 80 peer-reviewed articles (10 of which have won best paper awards) and is regularly invited to speak at venues across the world.  Lehman is currently a post-doctoral fellow at the University of Texas at Austin. In August 2015 he begins as an assistant professor at the IT University of Copenhagen.

Liberating message: Not all pursuits require an objective to justify them

Questioning foundational assumptions: The way we typically think about achievement could be wrong

Novel scientific argument: Evidence is provided from experiments with computers

Social benefits: New approaches to perennial problems are suggested

Accessible style: Written to appeal to novices and experts alike