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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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Proceedings Article
Shall We Repair? Genetic AlgorithmsCombinatorial Optimizationand Feasibility Constraints
David Orvosh,Lawrence Davis +1 more
TL;DR: This book aims to provide a chronology of the natural disasters that have affected the use of nuclear weapons in the United States over the years and some of the incidents are described.
Journal ArticleDOI
What is biomedical informatics
TL;DR: This work defines informatics as the science of information, where information is data plus meaning, which distinguishes the field from related fields, such as computer science, statistics and biomedicine, which have different objects of study.
Book ChapterDOI
On the locality of grammatical evolution
Franz Rothlauf,Marie Oetzel +1 more
TL;DR: The results show that the representation used in GE has problems with locality as many neighboring genotypes do not correspond to neighboring phenotypes, and it leads to lower performance for mutation-based search approaches in comparison to standard GP representations.
Journal ArticleDOI
State-of-the-art in empirical modelling of rapid prototyping processes
TL;DR: In this paper, a powerful modeling technique using genetic programming (GP) for modelling the FDM process is introduced and the issues related to the empirical modelling of RP processes are discussed, and the authors aim to investigate the performance of various potential empirical modelling techniques so that the choice of an appropriate modelling technique for a given RP process can be made.
Initializing the Particle Swarm Optimizer Using the Nonlinear Simplex Method
TL;DR: The Nonlinear Simplex Method is used to initialize the swarm of the Particle Swarm technique, implying that better convergence rates and success rates can be achieved by initializing the swarm this way.
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.