Augmented interactive evolutionary computation for composition
by Motoki Kamitani, Tadashi Ae
International Journal of Technology, Policy and Management (IJTPM), Vol. 4, No. 4, 2004

Abstract: In this paper, we propose an augmented interactive evolutionary computation technique to generate a symbol sequence, which is composed of several partial sequences. We introduce two-levels of feedback mechanism for evaluations, where the inner cycle induces an evolution of prediction agent for evaluation realised by a hidden Markov model, and the outer cycle induces an interaction with the user by selecting the candidate generated by the prediction agent. We describe, first, the process of augmented interactive evolutionary computation, and discuss the cooperative generation of sequences, which affects an anticipatory effective creation of formed sequence such as a music score. Next, we show several experimental results, which provide the generation of partial sequences and formed sequence.

Online publication date: Mon, 28-Mar-2005

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