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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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Automatic Re-engineering of Software Using Genetic Programming
TL;DR: This paper aims to provide a history of genetic programming and its applications in the context of software re-Engineering, and some of the techniques used in that process are described.
BookDOI
Benchmarking in tourism and hospitality industries : the selection of benchmarking partners
TL;DR: A general review of benchmarking benchmarking in the hotel industry measuring business performance is presented in this paper, where a mixture regression model data envelopment analysis evolutionary data envelope analysis (EDEA) is used.
Proceedings ArticleDOI
Applying genetic algorithms to decision making in autonomic computing systems
TL;DR: This paper proposes an approach to leverage genetic algorithms in the decision-making process of an autonomic system that enables a system to dynamically evolve reconfiguration plans at run time in response to changing requirements and environmental conditions.
Journal ArticleDOI
Intelligent Skin Cancer Detection Using Enhanced Particle Swarm Optimization
TL;DR: This research undertake intelligent skin cancer diagnosis based on dermoscopic images using a variant of the Particle Swarm Optimization algorithm that shows a superior performance over those of other advanced and classical search methods for identifying discriminative features that facilitate benign and malignant lesion classification and for solving diverse optimization problems with different landscapes.
Journal ArticleDOI
Soft computing techniques in structural and earthquake engineering: a literature review
TL;DR: A state-of-the-art review of the main applications of soft computing techniques to relevant structural and earthquake engineering problems is proposed, including the applications of fuzzy computing, evolutionary computing, swarm intelligence, and neural networks.
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.