Genetic Programming Theory and Practice 2010: An Introduction

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InCollection{McConaghy:2010:intro,
  author =       "Trent McConaghy and Ekaterina Vladislavleva and 
                 Rick Riolo",
  title =        "Genetic Programming Theory and Practice 2010: An
                 Introduction",
  booktitle =    "Genetic Programming Theory and Practice VIII",
  year =         "2010",
  editor =       "Rick Riolo and Trent McConaghy and 
                 Ekaterina Vladislavleva",
  series =       "Genetic and Evolutionary Computation",
  volume =       "8",
  address =      "Ann Arbor, USA",
  month =        "20-22 " # may,
  publisher =    "Springer",
  pages =        "xvii--xxviii",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4419-7746-5",
  URL =          "http://www.springer.com/computer/ai/book/978-1-4419-7746-5",
  URL =          "http://trent.st/content/2010-GPTP-introduction.pdf",
  size =         "12 pages",
  abstract =     "The toy problems are long gone, real applications are
                 standard, and the systems have arrived. Genetic
                 programming (GP) researchers have been designing and
                 exploiting advances in theory, algorithm design, and
                 computing power to the point where (traditionally) hard
                 problems are the norm. As GP is being deployed in more
                 real-world and hard problems, GP research goals are
                 evolving to a higher level, to systems in which GP
                 algorithms play a key role. The key goals in GP
                 algorithm design are reasonable resource usage,
                 high-quality results, and reliable convergence. To
                 these GP algorithm goals, we add GP system goals: ease
                 of system integration, end-user friendliness, and user
                 control of the problem and interactivity. In this book,
                 expert GP researchers demonstrate how they have been
                 achieving and improving upon the key GP algorithm and
                 system aims, to realize them on real-world / hard
                 problems. This work was presented at the GP Theory and
                 Practice (GPTP) 2010 workshop. This introductory
                 chapter summarises how these experts' work is driving
                 the frontiers of GP algorithms and GP systems in their
                 application to ever-harder application domains.",
  notes =        "part of \cite{Riolo:2010:GPTP}",
}

Genetic Programming entries for Trent McConaghy Ekaterina (Katya) Vladislavleva Rick L Riolo

Citations