Memetic Music Composition

作者：Munoz Enrique^*; Cadenas Jose Manuel^*; Ong Yew Soon^*; Acampora Giovanni^*

来源：IEEE Transactions on Evolutionary Computation, 2016, 20(1): 1-15.

DOI：10.1109/TEVC.2014.2366871

• Adaptive memetic algorithms
• automatic music composition
• multiagent systems

Computers and artificial intelligence play a key role in the production of artwork through the designing of synthetic agents that are able to reproduce the capabilities of human artists in assembling high-quality artefacts such as paintings and sculptures. In this context, music composition represents one of the art disciplines that can greatly benefit from the appropriate use of computational intelligence, as witnessed by the large number of research activities performed in this field over the recent years. Nevertheless, the automatic composition of music is far from being completely and precisely perfected due to the intrinsic virtuosity that characterizes human musicians' capabilities. This paper reduces this gap with the proposal of an intelligent scheme for the efficient composition of melodies based on a musical method that is inspired by and strongly characterized by human virtuosity: the unfigured bass technique. In particular, we formulate this music composition technique as an optimization problem and solve it with an adaptive multi-agent memetic approach comprising diverse metaheuristics, the composer agents that cooperate to create high-quality four-voice pieces of music starting from a bass line as input. A collection of experimental studies on the famous Bach's four-voice chorales showed that the cooperation among different optimization strategies yields improved performance over the solutions obtained by conventional and hybrid evolutionary algorithms.

• 出版日期2016-2