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Handbook of Grammatical Evolution (Hardcover, 1st ed. 2018)
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Handbook of Grammatical Evolution (Hardcover, 1st ed. 2018)
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This handbook offers a comprehensive treatise on Grammatical
Evolution (GE), a grammar-based Evolutionary Algorithm that employs
a function to map binary strings into higher-level structures such
as programs. GE's simplicity and modular nature make it a very
flexible tool. Since its introduction almost twenty years ago,
researchers have applied it to a vast range of problem domains,
including financial modelling, parallel programming and genetics.
Similarly, much work has been conducted to exploit and understand
the nature of its mapping scheme, triggering additional research on
everything from different grammars to alternative mappers to
initialization. The book first introduces GE to the novice,
providing a thorough description of GE along with historical key
advances. Two sections follow, each composed of chapters from
international leading researchers in the field. The first section
concentrates on analysis of GE and its operation, giving valuable
insight into set up and deployment. The second section consists of
seven chapters describing radically different applications of GE.
The contributions in this volume are beneficial to both novices and
experts alike, as they detail the results and researcher
experiences of applying GE to large scale and difficult problems.
Topics include: * Grammar design * Bias in GE * Mapping in GE *
Theory of disruption in GE * Structured GE * Geometric semantic GE
* GE and semantics * Multi- and Many-core heterogeneous parallel GE
* Comparing methods to creating constants in GE * Financial
modelling with GE * Synthesis of parallel programs on multi-cores *
Design, architecture and engineering with GE * Computational
creativity and GE * GE in the prediction of glucose for diabetes *
GE approaches to bioinformatics and system genomics * GE with
coevolutionary algorithms in cybersecurity * Evolving behaviour
trees with GE for platform games * Business analytics and GE for
the prediction of patient recruitment in multicentre clinical
trials
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