This chapter is about computational modelling of the process of musical composition, based on a cognitive model of human behaviour. The idea is to try to study not only the requirements for a computer system which is capable of musical composition, but also to relate it to human behaviour during the same process, so that it may, perhaps, work in the same way as a human composer, but also so that it may, more likely, help us understand how human composers work. Pearce et al. (2002) give a fuller discussion of the motivations behind this endeavour. \ud \ud We take a purist approach to our modelling: we are aiming, ultimately, at a computer system which we can claim to be creative. Therefore, we must address in advance the criticism that usually arises in these circumstances: “a computer can’t be creative because it can only do what it has explicitly been programmed to do”. This argument does not hold, because, with the advent of machine learning, it is no longer true that a computer is limited to what its programmer explicitly tells it, especially in an unsupervised learning task like composition (as compared with the usually-supervised task of learning, say, the piano). Thus, a creative system based on machine learning can, in principle, be given credit for creative output, much as Wolfgang Amadeus Mozart is deemed the creator of the Magic Flute, and not Leopold Mozart,Wolfgang’s father, teacher and de facto agent
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