Describes an award-winning evolutionary algorithm used for solving practical problems in industry
Provides a practical guide on using the uGP, a set of examples to clarify the available choices and advice against common errors and misconceptions
Offers practical knowledge about applying various evolutionary schemes using the toolkit, and a set of useful rules of thumb for tuning all toolkit capabilities
This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled uGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.
For a practitioner, uGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.
For an evolutionary computation researcher, uGP may be regarded as a platform where new operators and strategies can be easily tested.
MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
Evolutionary computation.- Why yet another one evolutionary optimizer?.- The uGP architecture.- Advanced features.- Performing an evolutionary run.- Command line syntax.- Syntax of the settings file.- Syntax of the population parameters file.- Syntax of the external constraints file.- Writing a compliant evaluator.- Implementation details.- Examples and applications.- Argument and option synopsis.- External constraints synopsis.- Index.- References
From the reviews:
"The text is a handbook for µGP. It is aimed at providing the reader with all of the information required for proficient use of the tool. ... At the end of the book, a chapter presents a number of examples and applications. ... the book meets its main objective of being a reference for the µGP tool ... . It is effective as a starting guide for using the tool, and is also useful for discovering advanced features and exploiting the flexibility of individual representation.” (Corrado Mencar, ACM Computing Reviews, March, 2012)
This text begins with an overview of the most popular techniques of evolutionary computation followed by a discussion of the theoretical and practical aspects of miGP. It includes several detailed examples with actual results.
This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled miGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.
For a practitioner, miGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.
For an evolutionary computation researcher, miGP may be regarded as a platform where new operators and strategies can be easily tested.
MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
Evolutionary computation.- Why yet another one evolutionary optimizer?.- The miGP architecture.- Advanced features.- Performing an evolutionary run.- Command line syntax.- Syntax of the settings file.- Syntax of the population parameters file.- Syntax of the external constraints file.- Writing a compliant evaluator.- Implementation details.- Examples and applications.- Argument and option synopsis.- External constraints synopsis.- Index.- References
From the reviews:
"The text is a handbook for µGP. It is aimed at providing the reader with all of the information required for proficient use of the tool. ... At the end of the book, a chapter presents a number of examples and applications. ... the book meets its main objective of being a reference for the µGP tool ... . It is effective as a starting guide for using the tool, and is also useful for discovering advanced features and exploiting the flexibility of individual representation." (Corrado Mencar, ACM Computing Reviews, March, 2012)
Inhaltsverzeichnis
Evolutionary computation.- Why yet another one evolutionary optimizer?.- The µGP architecture.- Advanced features.- Performing an evolutionary run.- Command line syntax.- Syntax of the settings file.- Syntax of the population parameters file.- Syntax of the external constraints file.- Writing a compliant evaluator.- Implementation details.- Examples and applications.- Argument and option synopsis.- External constraints synopsis.- Index.- References
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Klappentext
This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled µGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.
For a practitioner, µGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.
For an evolutionary computation researcher, µGP may be regarded as a platform where new operators and strategies can be easily tested.
MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
Describes an award-winning evolutionary algorithm used for solving practical problems in industry
Provides a practical guide on using the µGP, a set of examples to clarify the available choices and advice against common errors and misconceptions
Offers practical knowledge about applying various evolutionary schemes using the toolkit, and a set of useful rules of thumb for tuning all toolkit capabilities
Includes supplementary material: sn.pub/extras
