Handbook of Grammatical Evolution - Conor Ryan, Michael ONeill & J.J. Collins

By Conor Ryan, Michael ONeill & J.J. Collins

Release Date: 2018-09-11

Genre: Computers & Internet

(0 ratings)
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:

โ€ข         Grammar design
โ€ข         Bias in GE
โ€ข         Mapping in GE

โ€ข         Theory of disruption in GE

ยท               Structured GE
ยท               Geometric semantic GE
ยท               GE and semantics

ยท               Multi- and Many-core heterogeneous parallel GE

ยท               Comparing methods to creating constants in GE

ยท               Financial modelling with GE

ยท               Synthesis of parallel programs on multi-cores

ยท               Design, architecture and engineering with GE

ยท               Computational creativity and GE

ยท               GE in the prediction of glucose for diabetes

ยท              GE approaches to bioinformatics and system genomics

ยท               GE with coevolutionary algorithms in cybersecurity
ยท               Evolving behaviour trees with GE for platform games
ยท               Business analytics and GE for the prediction of patient recruitment in multicentre clinical trials

Handbook of Grammatical Evolution - Conor Ryan, Michael ONeill & J.J. Collins

By Conor Ryan, Michael ONeill & J.J. Collins

Release Date: 2018-09-11

Genre: Computers & Internet

(0 ratings)
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:

โ€ข         Grammar design
โ€ข         Bias in GE
โ€ข         Mapping in GE

โ€ข         Theory of disruption in GE

ยท               Structured GE
ยท               Geometric semantic GE
ยท               GE and semantics

ยท               Multi- and Many-core heterogeneous parallel GE

ยท               Comparing methods to creating constants in GE

ยท               Financial modelling with GE

ยท               Synthesis of parallel programs on multi-cores

ยท               Design, architecture and engineering with GE

ยท               Computational creativity and GE

ยท               GE in the prediction of glucose for diabetes

ยท              GE approaches to bioinformatics and system genomics

ยท               GE with coevolutionary algorithms in cybersecurity
ยท               Evolving behaviour trees with GE for platform games
ยท               Business analytics and GE for the prediction of patient recruitment in multicentre clinical trials

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