Furthermore, we utilize a supervised training scheme that uses Genetic Algorithms (GA) to evolve the rules of L and FL–systems, so that they may compose rhythms with certain characteristics. This work examines the composition of rhythms through L and Finite L–systems (FL–systems) and presents an inter-pretation from grammatical to rhythmic entities that ex-presses the repetitiveness and diversity of the output of these systems. However, the complexity imposed by un-supervised algorithms may arguably be considered as unde-sired, especially when considering the composition of rhythms. Music composition with algorithms inspired by nature has led to the creation of systems that compose music with rich characteristics. The results obtained by subjective tests indicate that the utilization of the proposed genetic operators drives the evolution to more user–preferable sounds. A modification of the GP operators is proposed that allows the user to have control on the randomness of the evolutionary process. This paper addresses this issue by presenting an IE system that evolves melodies us-ing Genetic Programming (GP). For the automatic creation of art and especially for music synthesis, user fatigue requires that the evolutionary process produces interesting con-tent that evolves fast. This kind of human–machine interaction be-longs to a larger methodological context called Interac-tive Evolution (IE). The introduction of Evolutionary Computation has further boosted the research towards exploring ways to incorporate human supervision and guidance in the automatic evolution of melodies and sounds. Additionally, how may we be able to compare the compositional capabilities of two such systems? Is there an objective criterion to characterize how “pleasant” is the music produced by such a machine?Īutomatic music composition and sound syn-thesis is a field of study that gains continuously in-creasing attention. This fact raises the question of how we may be sure that an automatic composition system composes too simple or too complex music. Nevertheless, almost everyone can more easily express an opinion about the complexity of a certain music excerpt. Referring to the terms “simple” and “complex,” someone may find her/himself sort of words when speaking about music. The intriguing part of automatic composition is the process of formulating such algorithms, in such a manner that the composed music is not too simple or too complex. The implementation of systems that perform this task, incorporates an algorithmic part which makes decisions on which notes/sounds will be heard, when they will be heard, for how long and how loud. The overall synthesis process is controlled by the conductor, a virtual entity that determines the syn- thesis evolution in a way that is very similar to directing an ensemble performance in real world.Īutomatic music composition is an enchanting field of research, inspiring both researchers and musicians. This complex mapping scheme allows the produc- tion of interesting and complicated sonic patterns that fol- low the performance evolution in both objective and con- ceptual levels. Finally, sound synthesis is achieved through a complex mapping scheme established between the events occurring in the Lake and the rhythmic, harmonic and dynamic-range pa- rameters of an advanced, collaborative sound composition engine. Multiuser intervention is employed in parallel, affecting the automated decisions and the physical parameters of the tribes, thus infusing the gaming orientation of the application context.
Tribes’ populations also demonstrate a number of physical properties that re- strict their ability to act illimitably. The tribes exhibit primitive social swarm-based behavior and intelli- gence, which is used for taking actions that will potentially allow to dominate the game world.
We use bio- inspired intelligence for developing a world - the Lake - where multiple tribes of artificial, autonomous agents live within, having survival as their ultimate goal. In this work we aim to combine a game platform with the concept of collaborative music synthesis.
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