Analysing psychological data by evolving computational models

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Peter C. R. Lane and Peter D. Sozou and 
                 Fernand Gobet and Mark Addis",
  title =        "Analysing psychological data by evolving computational
  booktitle =    "European Conference on Data Analysis (ECDA 2014) and
                 Workshop on Classification and Subject Indexing in
                 Library and Information Science (LIS 2014)",
  year =         "2014",
  editor =       "Adalbert F. X. Wilhelm and Hans A. Kestler",
  series =       "Studies in Classification, Data Analysis, and
                 Knowledge Organization",
  pages =        "587--597",
  address =      "Jacobs University, Bremen, Germany",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-25224-7",
  URL =          "",
  DOI =          "doi:10.1007/978-3-319-25226-1_50",
  abstract =     "We present a system to represent and discover
                 computational models to capture data in psychology. The
                 system uses a Theory Representation Language to define
                 the space of possible models. This space is then
                 searched using genetic programming (GP), to discover
                 models which best fit the experimental data. The aim of
                 our semi-automated system is to analyse psychological
                 data and develop explanations of underlying processes.
                 Some of the challenges include: capturing the
                 psychological experiment and data in a way suitable for
                 modelling, controlling the kinds of models that the GP
                 system may develop, and interpreting the final results.
                 We discuss our current approach to all three
                 challenges, and provide results from two different
                 examples, including delayed-match-to-sample and visual
  notes =        "Analysis of Large and Complex Data, Studies in
                 Classification, Data Analysis, and Knowledge
                 Organization, Proceedings of ECDA 2014.

                 Published 2016",

Genetic Programming entries for Peter C R Lane Peter D Sozou Fernand Gobet Mark Addis