- 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",
