A Hierarchical system for autonomous musical creation

M. Anthony Reimer, Guy E Garnett

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe work in progress on the development of a new hierarchical model of machine creativity operating in the domain of music. Similar to the way human brains work, our system separates low-level components associated with pattern recognition and analysis from the high-level creative components in two extensible layers. Separating this functionality in different layers of our system provides better visibility into the behavior of the creative component. This increased visibility has led to many improvements over previous iterations including the reward calculation for the creative component. Additionally, the design of an abstract input feature layer allows for greater flexibility in the number and combination of low-level features that can be used within our system.

Original languageEnglish (US)
Title of host publicationMusical Metacreation - Papers from the 2014 AIIDE Workshop, Technical Report
PublisherAI Access Foundation
Pages45-49
Number of pages5
ISBN (Electronic)9781577356875
StatePublished - Jan 1 2014
Event10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2014 - Raleigh, United States
Duration: Oct 4 2014 → …

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-14-18

Other

Other10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2014
CountryUnited States
CityRaleigh
Period10/4/14 → …

ASJC Scopus subject areas

  • Engineering(all)

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