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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
Soft computing for autonomous robotic systems
TL;DR: Three dominant hybrid approaches to intelligent control are experimentally applied to address various robotic control issues which are currently under investigation at the NASA Center for Autonomous Control Engineering.
BookDOI
Information Processing in Cells and Tissues
Mike Holcombe,Ray Paton +1 more
TL;DR: A notation for a hierarchical structure of the natural sciences is created which is consistent with categorical logic and a notational sequence for composing one to one correspondences among the degrees of organization of a cellular system is proposed.
Proceedings ArticleDOI
Perhaps not a free lunch but at least a free appetizer
TL;DR: It is argued why the scenario on which the No Free Lunch Theorem is based does not model real life optimization, and why optimization techniques differ in their efficiency.
Book ChapterDOI
Introduction to creative evolutionary systems
Peter J. Bentley,David Corne +1 more
TL;DR: In computer science and in artificial intelligence, when we use a search algorithm, we define a computational problem in terms of a search space, which can be viewed as a massive collection of potential solutions to the problem as mentioned in this paper.
Journal ArticleDOI
Data-driven modeling approaches to support wastewater treatment plant operation
David J. Dürrenmatt,Willi Gujer +1 more
TL;DR: A procedure to build software sensors based on sensor data available in the process information system is defined and used to compare several techniques suitable for data-driven modeling, including generalized least squares regression, artificial neural networks, self-organizing maps and random forests.
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.