Abstract
A scientific theory is developed by modelling empirical data in a range of domains. The goal of developing a theory is to optimise the t of the theory to as many experimental settings as possible, whilst retaining some qualitative properties such as `parsimony' or `comprehensibility'. We formalise the task of developing theories of human cognition as a problem in multi-criteria optimisation. There are many challenges in this task, including the representation of competing theories, coordinating the t with multiple experiments, and bringing together competing results to provide suitable theories. Experiments demonstrate the development of a theory of categorisation, using multiple optimisation criteria in genetic algorithms to locate pareto-optimal sets.
| Original language | English |
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| Title of host publication | In: Proceedings of the 2005 UK Workshop on Computational Intelligence |
| Publisher | Birkbeck |
| Pages | 28-35 |
| Publication status | Published - 2005 |