@inproceedings{67c6b4dccacd43cbbd87b4e56c6b273b,
title = "A Hierarchical system for autonomous musical creation",
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.",
author = "Reimer, {M. Anthony} and Garnett, {Guy E.}",
note = "Publisher Copyright: {\textcopyright} Copyright 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2014 ; Conference date: 04-10-2014",
year = "2014",
language = "English (US)",
series = "AAAI Workshop - Technical Report",
publisher = "AI Access Foundation",
pages = "45--49",
booktitle = "Musical Metacreation - Papers from the 2014 AIIDE Workshop, Technical Report",
}