Evolutionary computation (Dumitrescu, Lazzerini, Jain & Dumitrescu, 2000) is a subfield of artificial intelligence (more particularly computational intelligence) that can be defined by the type of algorithms it is concerned with. These algorithms, called evolutionary algorithms, are based on adopting the Darwinian principle of “survival of the fittest”. Evolutionary computation is a relatively new field of study, with its roots in the 1950s and a steady growth of interest from the 1970s onwards.
Evolutionary computation has proven capable of delivering high-quality solutions to difficult problems in a variety of scientific and technical domains (Eiben & Smith, 2015). Whilst much of the focus of research in this area has been related to solving numerical and combinatorial optimisation problems, the stochastic nature of evolutionary algorithms has been shown to have particular advantages in other fields. In particular, the lack of problem-specific preconceptions and biases of the algorithm designer open the door to the consideration of unexpected solutions (Bentley & Corne, 2002; Romero & Machado, 2007).
This special issue solicits high-quality papers that explore contemporary applications of evolutionary computation in the creative industries. In particular, this special issue seeks to explore the interface between man and machine, where research outcomes provide insight as to how evolutionary computation can augment or support human creativity.
The areas of interest to the special issue are divided into two main directions, albeit not exclusive:
- Creative exploration systems that support the concept of search without necessarily embracing a need for optimality
- Systems that utilise both human and non-human agents in the evolution of creative artefacts
In particular, this special issue seeks to present applications of evolutionary computation throughout the range of creative industries, including advertising, architecture, art, design, fashion, film, gaming, music, performing arts and software development.
Bentley, P., & Corne, D. (2002). Creative evolutionary systems. Burlington, MA: Morgan Kaufmann. Dumitrescu, D., Lazzerini, B., Jain, L. C., & Dumitrescu, A. (2000). Evolutionary computation. Boca
Raton, FL: CRC Press.
Eiben, A. E., & Smith, J. (2015). From evolutionary computation to the evolution of things. Nature, 521(7553), 476-482.
Romero, J. J., & Machado, P. (2007). The art of artificial evolution: A handbook on evolutionary art and music. Berlin: Springer
Suitable topics include, but are not limited to, the following application areas of evolutionary algorithms:
- Interactive evolutionary computation
- Human-based genetic algorithms
- Representation issues for evolutionary computation
- Creative exploration systems
- Novel evolutionary computation algorithms
- New ways of integrating the user in the evolutionary cycle
- Empirical and comparative studies
- Creative evolutionary design
- Evolutionary interactive art
- Evolutionary innovation
- Co-evolution and collective behaviour
Submission of manuscripts: 29 July, 2016
First notification to authors: 16 September, 2016
Final versions due: 9 December, 2016