Genetic Programming Theory and Practice XI

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Proceedings{Riolo:2013:GPTP,
  title =        "Genetic Programming Theory and Practice XI",
  year =         "2013",
  editor =       "Rick Riolo and Jason H. Moore and Mark Kotanchek",
  series =       "Genetic and Evolutionary Computation",
  address =      "Ann Arbor, USA",
  month =        "9-11 " # may,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Artificial
                 evolution, Evolution of models, Feature selection,
                 Genetic programming applications, Genetic programming
                 theory, Program induction, Symbolic regression",
  isbn13 =       "978-1-4939-0374-0",
  URL =          "http://www.springer.com/computer/ai/book/978-1-4939-0374-0",
  size =         "226 pages",
  notes =        "Table of contents:

                 -Extreme Accuracy in Symbolic Regression
                 \cite{Korns:2013:GPTP}.

                 -Exploring Interestingness in a Computational Evolution
                 System for the Genome-Wide Genetic Analysis of
                 Alzheimer's Disease \cite{Moore:2013:GPTP}.

                 -Optimising a Cloud Contract Portfolio using Genetic
                 Programming-based Load Models
                 \cite{Stijven:2013:GPTP}.

                 -Maintenance of a Long Running Distributed Genetic
                 Programming System for Solving Problems Requiring Big
                 Data \cite{Hodjat:2013:GPTP}.

                 -Grounded Simulation: Using Simulated Evolution to
                 Guide Embodied Evolution
                 \cite{Ryan:2013:GPTP}.

                 -Applying Genetic Programming in Business Forecasting
                 \cite{Kordon:2013:GPTP}.

                 -Explaining Unemployment Rates with Symbolic Regression
                 \cite{Truscott:2013:GPTP}.

                 -Uniform Linear Transformation with Repair and
                 Alternation in Genetic Programming
                 \cite{Spector:2013:GPTP}.

                 -A Deterministic and Symbolic Regression Hybrid Applied
                 to Resting-State fMRI Data.
                 \cite{Icke:2013:GPTP}

                 -Gaining Deeper Insights in Symbolic Regression
                 \cite{Affenzeller:2013:GPTP}.

                 -Geometric Semantic Genetic Programming for Real Life
                 Applications \cite{Vanneschi:2013:GPTP}.

                 -Evaluation of Parameter Contribution to Neural Network
                 Size and Fitness in ATHENA for Genetic Analysis
                 \cite{Li:2013:GPTP}.

                 Published 2014",
}

Genetic Programming entries for Rick L Riolo Jason H Moore Mark Kotanchek

Citations