The development of scientific models suffers from two related problems: the ever-growing number of experimental results and scientists’ cognitive limitations (including cognitive biases). This multidisciplinary project (psychology, philosophy, computer modelling, computer science and cognitive neuroscience) addresses these problems by developing a novel methodology for generating scientific models automatically. The methodology is not specific to any particular discipline and can be applied to any science where experimental data are available. The method treats models as computer programs and evolves a population of models using genetic programming. The extent to which the models fit the empirical data is used as a fitness function. The best models – potentially modified by cross-over and mutation – are selected for the next generation. Pilot simulations have established the validity of the methodology with simple experiments in psychology.
This project is funded by a five-year European Research Council (ERC) Advanced Grant.
Project’s webpage: https://gems-science.netlify.app/
Fernand Gobet
Fernand Gobet is the leader of the GEMS project. He earned in PhD in 1992 at the University of Fribourg, Switzerland. After collaborating with Nobel laureate Herbert Simon for six years at Carnegie Mellon, Pittsburgh, he was lecturer and then reader at the University of Nottingham. He then held professorships at Brunel University London and the University of Liverpool. His research interests include the psychology of expertise and talent, scientific discovery, computational modelling and the acquisition of language. His research has combined experimental methods, philosophical analysis, brain imaging, computational modelling and qualitative methods. He is the main architect behind the CHREST (Chunk Hierarchy and REtrieval STructures) cognitive architecture. Along with other books on expertise, computational modelling and cognitive psychology, he is the author ofUnderstanding expertise: A multi-disciplinary approach (2016, Palgrave/Macmillan) and The psychology of chess (2018, Routledge), and co-editor of Scientific Discovery in the Social Sciences (2019, Springer)
Email: F.Gobet@lse.ac.uk
Laura Barlett
Laura Bartlett is a postdoctoral researcher in the GEMS project. She recently completed her PhD investigating the effects of attention on sensory adaptation, supervised by Professor Wendy Adams and Dr Erich Graf at the University of Southampton. Her research interests include visual and haptic perception, adaptation and attention.
Email: L.Bartlett@lse.ac.uk
Dmitry Bennett
Dmitry Bennett is a postdoctoral researcher in the GEMS project. He will be developing computational models of categorisation by merging basic mechanisms and processes of cognitive psychology with the genetic/evolutionary approach.
Dmitry earned his PhD from the University of Liverpool in 2022 under the supervision of Fernand Gobet and Julian Pine. His research interests span Single Algorithm Hypothesis in context of the brain, psychologically plausible models of concept learning and modelling subjectivity in human simulations. His current focus is on the interaction of genetic and cognitive/neural algorithms.
email: D.Bennett5@lse.ac.uk
Nomad Javed
Noman Javed is a Research Officer in the GEMS project. He earned his Ph.D. at the University of Orleans (France), working with Prof Frederic Loulergue in the area of Parallel Computing. He then completed a postdoc at the University of Edinburgh (UK), working with Prof Murray Cole in the area of automatic parallelization of legacy code. He then joined Namal Institute Mianwali, Pakistan as Assistant Professor of Computer Science. His research interests include evolutionary computing and making it computationally feasible using parallel computing.
Email: n.javed3@lse.ac.uk
Angelo Pirrone
From 2023-23, Angelo Pirrone was a Research Officer in the GEMS project. He earned his PhD at the University of Sheffield (UK), working with Dr Tom Stafford and Prof James Marshall on adaptive decision making and cognitive modelling. He then completed a postdoc at Peking University (China), working with Prof Sheng Li on elucidating the neural substrates of perceptual decision making, and a short postdoc at the University of Bergen (Norway). His research interests include computational modelling, decision making and learning. His research combines experimental methods, computational modelling, evolutionary theory and brain imaging.