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Genetic Programming: On the Programming of Computers by Means of Natural Selection
TLDR
This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.Abstract:
Background on genetic algorithms, LISP, and genetic programming hierarchical problem-solving introduction to automatically-defined functions - the two-boxes problem problems that straddle the breakeven point for computational effort Boolean parity functions determining the architecture of the program the lawnmower problem the bumblebee problem the increasing benefits of ADFs as problems are scaled up finding an impulse response function artificial ant on the San Mateo trail obstacle-avoiding robot the minesweeper problem automatic discovery of detectors for letter recognition flushes and four-of-a-kinds in a pinochle deck introduction to biochemistry and molecular biology prediction of transmembrane domains in proteins prediction of omega loops in proteins lookahead version of the transmembrane problem evolutionary selection of the architecture of the program evolution of primitives and sufficiency evolutionary selection of terminals evolution of closure simultaneous evolution of architecture, primitive functions, terminals, sufficiency, and closure the role of representation and the lens effect Appendices: list of special symbols list of special functions list of type fonts default parameters computer implementation annotated bibliography of genetic programming electronic mailing list and public repositoryread more
Citations
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What bloat? Cartesian Genetic Programming on Boolean problems
TL;DR: It is argued that an important factor in the analysis of the change of program length is neutral drift, and that if genotype redundancy is present, the genetic neutral drift simultaneously improves search and compresses program code.
Proceedings ArticleDOI
The relationship between search based software engineering and predictive modeling
TL;DR: The paper sets out eleven open problem areas for Search Based Predictive Modeling and describes how predictive models also have role to play in improving SBSE.
BookDOI
Soft Computing for Knowledge Discovery and Data Mining
Oded Maimon,Lior Rokach +1 more
TL;DR: This edited volume by highly regarded authors, includes several contributors of the 2005, Data Mining and Knowledge Discovery Handbook and is suitable as a secondary textbook or reference for advanced-level students in information systems, engineering, computer science and statistics management.
Journal ArticleDOI
Genotype-phenotype mapping: genes as computer programs.
TL;DR: The encoding of cellular and higher-order activities by genes is seen as directly analogous to computer programs and is of utility in biological genetics and in problems of genotype-phenotype mapping.
Journal ArticleDOI
The Use of an Analytic Quotient Operator in Genetic Programming
TL;DR: It is demonstrated that this AQ operator systematically yields lower mean squared errors over a range of regression tasks, due principally to removing the discontinuities or singularities that can often result from using either protected or unprotected division.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book ChapterDOI
Learning internal representations by error propagation
TL;DR: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion.
Book
Ecological Diversity and its Measurement
TL;DR: In this paper, the authors define definitions of diversity and apply them to the problem of measuring species diversity, choosing an index and interpreting diversity measures, and applying them to structural and structural diversity.
Book
The perception: a probabilistic model for information storage and organization in the brain
TL;DR: The second and third questions are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory as mentioned in this paper.