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Marsden and A. ), Computer Representation and Models in Music, Academic Press, 266-301, (1992). , Music and Schema Theory - Cognitive Foundations of Systematic Musicology, Springer Verlag (1995). , Schema-based tone centre recognition of musical signals. Journal of New Music Research, 23, 169-204, (1994). , Symbolic and subsymbolic descriptions of music. In G. ), Music Processing, Oxford University Press, 119-164, (1993). , Composing with chaos; applications of a new science for music. Interface, 22, 23-51, (1993).

Given a language for knowledge representation, we can sometimes say, in a very precise mathematical sense, how difficult reasoning about knowledge expressed in a particular language is. This means that, if we are careful, we can be in a position to choose the simplest possible kind of language required to represent and reason with our knowledge. , 1991). Representing Musical Knowledge Surfaces of Abstraction - the Musical Surface Another important question is a philosophical one: how do we choose the level of detail at which to work?

The importance of basic musical knowledge for effective learning. In M. Balaban, K. Ebcioglu, and 0. ), Understanding Music with AI Perspectives on Music Cognition, AAAI Press and MIT Press 490-507, (1992). , Linguistics and the computer analysis of tonal harmony. Journal of Music Theory, 12, 2-49, (1968). 3 MUSICAL KNOWLEDGE: WHAT CAN ARTIFICIAL INTELLIGENCE BRING TO THE MUSICIAN? Geraint Wiggins, Alan Smaill Introduction In this chapter, we introduce the field of Artificial Intelligence (AI), especially as it relates to music and musicology, and discuss an aspect of fundamental importance in its use for both theory and practice: the representation of knowledge, primarily for use on computers, but not necessarily so.

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