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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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Journal ArticleDOI
Empirical modeling of plate load test moduli of soil via gene expression programming
TL;DR: In this article, new empirical models were developed to predict the soil deformation moduli using gene expression programming (GEP) using a series of plate load tests conducted on different soil types at depths of 1-24m.
Journal ArticleDOI
Generalized Disjunction Decomposition for Evolvable Hardware
TL;DR: A new type of decomposition strategy for EHW, the "generalized disjunction decomposition" (GDD), which allows the evolution of large circuits never before evolved and reduces computational time.
Journal ArticleDOI
Tracking Fish Abundance by Underwater Image Recognition
Simone Marini,Emanuela Fanelli,Valerio Sbragaglia,Ernesto Azzurro,Joaquín del Río Fernandez,Jacopo Aguzzi +5 more
TL;DR: The automated recognition results were highly correlated with the manual counts and they were highly reliable when used to track fish variations at different hourly, daily, and monthly time scales, and could be easily transferred to other cabled video-observatories.
Journal ArticleDOI
Discrimination of the variety and region of origin of extra virgin olive oils using 13C NMR and multivariate calibration with variable reduction
Adrian D. Shaw,Angela di Camillo,Giovanna Vlahov,Alun Jones,Giorgio Bianchi,Jem J. Rowland,Douglas B. Kell +6 more
TL;DR: Eshuis et al. as discussed by the authors applied Principal Component Analysis (PCA), Principal Component Regression (PCR) and Partial Least Squares (PLS) to discriminate olive oils on the basis of their 13 C NMR spectra.
Journal ArticleDOI
Semantic Backpropagation for Designing Search Operators in Genetic Programming
TL;DR: It is indicated that semantic backpropagation helps evolution to identify the desired intermediate computation states and makes the search process more efficient.
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.