Patterns of Intuition Musical Creativity in the Light of Algorithmic Composition /

The present book is the result of a three year research project which investigated the creative act of composing by means of algorithmic composition. Central to the investigation are the compositional strategies of 12 composers, which were documented through a dialogic and cyclic process of modellin...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Nierhaus, Gerhard (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Dordrecht : Springer Netherlands : Imprint: Springer, 2015.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Patterns of Intuition  |h [electronic resource] :  |b Musical Creativity in the Light of Algorithmic Composition /  |c edited by Gerhard Nierhaus. 
264 1 |a Dordrecht :  |b Springer Netherlands :  |b Imprint: Springer,  |c 2015. 
300 |a VIII, 421 p. 197 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Outline of the compositional structure(s) to be investigated -- The algorithms/procedures used -- Findings -- Improvisation in Trees -- Electronic Music for an Acoustic Piano -- Forbidden Melodies -- The Semantics of a String Quartet -- Comments from renowned scientists from related research areas of Algorithmic Composition, Musicology, Artistic Research, Creativity. 
520 |a The present book is the result of a three year research project which investigated the creative act of composing by means of algorithmic composition. Central to the investigation are the compositional strategies of 12 composers, which were documented through a dialogic and cyclic process of modelling and evaluating musical materials. The aesthetic premises and compositional approaches configure a rich spectrum of diverse positions, which is reflected also in the kinds of approaches and methods used. These approaches and methods include the generation and evaluation of chord sequences using genetic algorithms, the application of morphing strategies to research harmonic transformations, an automatic classification of personal preferences via machine learning, and an application of mathematical music theory to the analysis and resynthesis of musical material. The second part of the book features contributions by Sandeep Bhagwati, William Brooks, David Cope, Darla Crispin, Nicolas Donin, and Guerino Mazzola. These authors variously consider the project from different perspectives, offer independent approaches, or provide more general reflections from their respective research fields. 
650 0 |a Computer science. 
650 0 |a Music. 
650 0 |a Artificial intelligence. 
650 0 |a System theory. 
650 0 |a Physics. 
650 0 |a Complexity, Computational. 
650 1 4 |a Computer Science. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Complex Networks. 
650 2 4 |a Complex Systems. 
650 2 4 |a Music. 
650 2 4 |a Complexity. 
700 1 |a Nierhaus, Gerhard.  |e editor. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9789401795609 
856 4 0 |u http://dx.doi.org/10.1007/978-94-017-9561-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)