Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
β Scribed by Michael OβNeill, Conor Ryan (auth.)
- Publisher
- Springer US
- Year
- 2003
- Tongue
- English
- Leaves
- 156
- Series
- Genetic Programming Series 4
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.
β¦ Table of Contents
Front Matter....Pages i-xvi
Introduction....Pages 1-4
Survey Of Evolutionary Automatic Programming....Pages 5-21
Lessons From Molecular Biology....Pages 23-32
Grammatical Evolution....Pages 33-47
Four Examples of Grammatical Evolution....Pages 49-62
Analysis of Grammatical Evolution....Pages 63-77
Crossover in Grammatical Evolution....Pages 79-98
Extensions & Applications....Pages 99-128
Conclusions & Future Work....Pages 129-132
Back Matter....Pages 133-144
β¦ Subjects
Artificial Intelligence (incl. Robotics); Theory of Computation; Computer Science, general
π SIMILAR VOLUMES
<p>This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism.<BR>This book introduces a new approach to th
<p>This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism.<BR>This book introduces a new approach to th
The topic of this book is the theoretical foundations of the theory LSLT - Lexical Semantic Language Theory - and its implementation in the system for text analysis and understanding called GETARUN, developed at the University of Venice, Laboratory of Computational Linguistics, Department of Languag
In comparing this book with, say Goldberg's "Genetic Algorithms..." (may be the most popular genetic algorithms text), this book reads more like a German habilitation thesis (which I imagine it may have served as such), where as Goldberg's book seems more of a light introduction for the mathematical