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Computational modelling of creativity in abstract art

Artistic creativity is studied through the construction of computational models of a number of well known modern artists. In particular, the work of Piet Modrian, M.C. Escher and Paul Klee are suitable vehicles for investigation since their work is accompanied by extensive writings describing the ideas and motivation behind their compositions. In particular, we have tried to abstract from their theories rules that describe the construction procoss or the properties that their finished artefacts possess in order to create software programmes that can articulate these rules. In this way we are able to simulate either automatically or with user interaction, the process of creating works of art of a similar genre and satisfying the properties desired by the artist. Since the rules are bound to be considerably more complex than those currently exposed we are looking to use machine learning techniques to develop more sophisticated agents whihc may behave more closely like the actual artist.