Ryan Conor Collins Jj (28 results)

Condition: New. In English.

Condition: New. In English.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Taschenbuch. Condition: Neu. Neuware -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 508 pp. Englisch.…

Condition: New. pp. 497.

Condition: As New. Unread book in perfect condition.

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Taschenbuch. Condition: Neu. Handbook of Grammatical Evolution | Conor Ryan (u. a.) | Taschenbuch | x | Englisch | 2019 | Springer | EAN 9783030087722 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condition: New.

Hardcover. Condition: Brand New. 497 pages. 9.25x6.25x1.25 inches. In Stock.

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: new. Questo è un articolo print on demand.

Condition: new. Questo è un articolo print on demand.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 508 pp. Englisch. …

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Examines the state of the art in Grammatical EvolutionDemonstrates a variety of significant applications for Grammatical Evoluation Provides literature review and reflection spanning two decades of research in the field.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Examines the state of the art in Grammatical EvolutionDemonstrates a variety of significant applications for Grammatical Evoluation Provides literature review and reflection spanning two decades of research in the field.…

Condition: New. Print on Demand pp. 497.

Condition: New. PRINT ON DEMAND pp. 497.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 trialsSpringer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 508 pp. Englisch.…

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿ Bias in GESpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 508 pp. Englisch.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.