Towards models of user preferences in interactive musical evolution

Costelloe, Dan; Ryan, Conor

doi:10.1145/1276958.1277389

Cited by 4 publications

(1 citation statement)

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“…Further illustrating the diversity of application, grammatical forms of GP have been applied in Bioinformatics (e.g., evolving regular expressions [49]), Software Cost Estimation [92], Robot Control [96], Music [15,10], Logic Programming [44], fuzzy control [74] and solving differential equations [99].…”

Section: Applicationsmentioning

confidence: 99%

Grammar-based Genetic Programming: a survey

McKay

Hoài

Whigham

et al. 2010

Genet Program Evolvable Mach

322

138

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Publication informationGenetic Programming and Evolvable Machines, Abstract Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP). Practical grammar-based GP systems first appeared in the mid 1990s, and have subsequently become an important strand in GP research and applications. We trace their subsequent rise, surveying the various grammar-based formalisms that have been used in GP and discussing the contributions they have made to the progress of GP. We illustrate these contributions with a range of applications of grammar-based GP, showing how grammar formalisms contributed to the solutions of these problems. We briefly discuss the likely future development of grammar-based GP systems, and conclude with a brief summary of the field.

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