- author = "Peter C. R. Lane and Peter D. Sozou and Fernand Gobet and Mark Addis",
- title = "Analysing psychological data by evolving computational models",
- 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 = "
https://link.springer.com/chapter/10.1007/978-3-319-25226-1_50",
-
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 attention.",
-
notes = "Analysis of Large and Complex Data, Studies in
Classification, Data Analysis, and Knowledge
Organization, Proceedings of ECDA 2014.
Published 2016",
