Grammatical Evolution Evolutionary Automatic Programming in an Arbitrary Language

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.

1. Introduction.- 1 Evolutionary Automatic Programming.- 2 Molecular Biology.- 3 Grammars.- 4 Outline.- 2. Survey of Evolutionary Automatic Programming.- 1 Introduction.- 2 Evolutionary Automatic Programming.- 3 Origin of the Species.- 4 Tree-based Systems.- 5 String based GP.- 6 Conclusions.- 3. Lessons from Molecular Biology.- 1 Introduction.- 2 Genetic Codes & Gene Expression Models.- 3 Neutral Theory of Evolution.- 4 Further Principles.- 5 Desirable Features.- 6 Conclusions.- 4. Grammatical Evolution.- 1 Introduction.- 2 Background.- 3 Grammatical Evolution.- 4 Discussion.- 5 Conclusions.- 5. Four Examples of Grammatical Evolution.- 1 Introduction.- 2 Symbolic Regression.- 3 Symbolic Integration.- 4 Santa Fe Ant Trail.- 5 Caching Algorithms.- 6 Conclusions.- 6. Analysis of Grammatical Evolution.- 1 Introduction.- 2 Wrapping Operator.- 3 Degenerate Genetic Code.- 4 Removal of Wrapping and Degeneracy.- 5 Mutation Rates.- 6 Conclusions.- 7. Crossover in Grammatical Evolution.- 1 Introduction.- 2 Homologous Crossover.- 3 Headless Chicken.- 4 Conclusions.- 8. Extensions & Applications.- 1 Translation.- 2 Alternative Search Strategies.- 3 Grammar Defined Introns.- 4 GAUGE.- 5 Chorus.- 6 Financial Prediction.- 7 Adaptive Logic Programming.- 8 Sensible Initialisation.- 9 Genetic Programming.- 10 Conclusions.- 9. Conclusions & Future Work.- 1 Summary.- 2 Future Work.