Open AccessBook
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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Journal ArticleDOI
Automatic analogue circuit synthesis using genetic algorithms
TL;DR: A new approach to circuit synthesis based on genetic algorithms is presented that produces design solutions that are more efficient than those resulting from formal design methods or created manually by an experienced analogue circuit designer.
Proceedings ArticleDOI
Metrics are fitness functions too
Mark Harman,John A. Clark +1 more
TL;DR: A brief survey of search-based approaches is presented and shows how metrics have been combined with the search based techniques to improve software systems and the benefits for metric analysis and validation which accrue from the MAFF approach.
Journal ArticleDOI
Breast cancer diagnosis using genetic programming generated feature
Hong Guo,Asoke K. Nandi +1 more
TL;DR: A novel method for breast cancer diagnosis using the feature generated by genetic programming based on Fisher criterion to transform information from high dimensional feature space into one dimensionality space and automatically discover the relationships among data, in order to improve classification accuracy.
Journal ArticleDOI
Genetic-Algorithm-Based Method for Optimal Analog Test Points Selection
T. Golonek,Jerzy Rutkowski +1 more
TL;DR: The described method uses ambiguity set concept and evolutionary computations to determine the optimal set of analog test points and the efficiency of the technique is compared with a method based on entropy index.
Journal ArticleDOI
A constrained-syntax genetic programming system for discovering classification rules: application to medical data sets
TL;DR: The proposed constrained-syntax genetic programming (GP) algorithm contains several syntactic constraints to be enforced by the system using a disjunctive normal form representation, so that individuals represent valid rule sets that are easy to interpret.
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.
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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.