CHREST (Chunk Hierarchy and REtrieval STructures) is a comprehensive computational model of human 
learning and perception (see http://www.chrest.info). It has been used to
successfully simulate data in a variety of domains, including: acquisition of syntactic categories,
expert behaviour, concept formation, implicit learning, and the acquisition of multiple representations
in physics for problem solving, and gambling. The aim of this workshop is to provide participants 
with an introduction to CHREST, how it can be used to model various phenomena, and the knowledge to
carry out their own modelling experiments. Participants in this tutorial will:

- Acquire a comprehensive understanding of the CHREST computational model and its relation to the 
chunking and template theories of cognition;
- Explore some key learning phenomena supporting the chunking theory by taking part in a verbal-learning experiment;
- Attempt to match the performance of a CHREST model of verbal learning with their own data; and
- Be introduced to the implementation of CHREST in sufficient detail to begin modelling data in their own domains

The tutorial is held by Prof. Fernand Gobet, Dr. Peter Lane, and Dr. Marvin Schiller.

Fernand Gobet (http://www.brunel.ac.uk/~hsstffg/) is Professor of Psychology at Brunel University. 
He previously was Reader of Intelligent Systems at the University of Nottingham. He started working
on the CHREST architecture in collaboration with Herbert Simon during his stay at Carnegie Mellon
(1990-1995). In addition to developing the CHREST architecture, his scientific interests include: 
methodology of computational modelling; empirical research into expert behaviour, including its 
neural correlates; the psychology of board games; problem gambling; natural and artifical 
intelligence; and the fusion between perceptual and conceptual knowledge.

Peter Lane (http://homepages.feis.herts.ac.uk/~comqpcl/)
is a Senior Lecturer in the School of Computer Science at the University of Hertfordshire. He was 
introduced to CHREST when working for Fernand Gobet at the University of Nottingham. In addition 
to work with CHREST, research interests include: data mining, image analysis and machine learning.

Marvin Schiller (http://www.marvin-schiller.de) is a Research Fellow at the Centre for the Study 
of Expertise at Brunel University. His current work investigates cognitive models of problem 
gambling using CHREST.

+++ Organisers +++

Fernand Gobet and Marvin Schiller, Brunel University, London, UK

+++ Further Information/Registration +++

Please see
http://www.gamblingresearch.net/chrest-tutorial
or contact the organisers.