The theory of cellular automata has been investigated and developed for over three decades. A class of mathematical models known as cellular automata play the central role in this research. As far as these questions are concerned, the work introduced in this paper is to be regarded only as a contribution for empirical experimentation. Each artist must make his/her own judgements. Obviously, there are no simple answers for these questions and indeed we do not intend to provide any here. However, their use raises certain questions like: What can be the justification for using science as a compositional tool? and Which aspects of science are applicable to music and how can it be done?.

Scientific models carry an important component of human thought, namely formal abstraction, which can be very inspiring for music composition. On the other hand scientists also seem to show interest in the organisational principles found in music. Today, it is becoming increasingly common for the composer to turn to the sciences to supplement his or her compositional model. Music has always been an interesting domain for the application of new scientific discoveries inviting composers to combine artistic creativity with scientific methods. The results were extracted by means of known musical information retrieval techniques. In order to validate the effectiveness as well as efficiency of the architecture, we present some results about the generated melodies. to maximize the applicability potential of the architecture, the configuration data that influence the generated music product is performed almost in entirety by the user, with no virtual limit of the number of possible melodic combinations generated by the hardware. The proposed architecture allows 16 possible combinations of cellular automata models. To this end, the architecture includes four kind of cellular automata, developed through four neighborhood models with a radius of 1. The implementation of the architecture is implemented in FPGA aiming at designing an alternative efficient tool for the study and research related to the field of random music. This paper proposes a hardware architecture to generate harmonized music, which is composed by melodic intervals determined from the association of cellular automata in accordance to standard MIDI protocol. As our research progressed, we have successfully harnessed the organism to implement a sound synthesiser and a musical sequencer, grow biological audio wires, and build an interactive biocomputer that can listen and produce musical responses in real-time. The organism is amorphous, and although without a brain or any serving centre of control, can respond to the environmental conditions that surround it. The plasmodium of Physarum polycephalum is a large single cell with a myriad of diploid nuclei, which moves like a giant amoeba in its pursuit for food. In this chapter, after a brief introduction to Unconventional Computing, we present our research into harnessing the behaviour of a slime mould called Physarum polycephalum to build new kinds of processors for audio and music. We are investigating how Unconventional Computing may benefit the future of the music industry and related audio engineering technologies. The emerging field of Unconventional Computing is developing new algorithms and computing architectures inspired by or implemented in biological, physical and chemical systems. Selective breeding, by a user judging evolved sounds, has been employed to guide the evolutionary processes, or attention has been focused on fitness functions used to drive the evolution, automatically matching a target sound using either a given synthesizer, evolved populations of sound waves or grown sound synthesizers using evolutionary methods, using custom descriptions of sound synthesis algorithms in the form of cyclic topology graphs and acyclic tree graphs with ordered branches. Cellular Automata (CA) have also been used to control over time the parameters of a synthesis instrument, whereby the emergent behaviour of CA is used to model generative processes for synthesised sound and musical forms.

Evolution of synthesizer parameters aims to facilitate an exploratory approach to sound design, addressing the problem of required intimate knowledge of sound synthesis techniques in order to design sounds that are novel and of musical interest, using genetic algorithms operating on the parameter settings of a synthesizer.

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