scispace - formally typeset
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 repository

read more

Citations
More filters
Journal ArticleDOI

Hybrid soft computing systems: industrial and commercial applications

TL;DR: In this article, a collection of methods and tools that can be used to perform diagnostics, estimation, and control of industrial equipment, freight train control, and residential property valuation are presented.
Journal ArticleDOI

A hierarchical clustering methodology based on genetic programming for the solution of simple cell-formation problems

TL;DR: In this paper the use of genetic programming for the solution of a simple version of the problem of identifying machine cells and corresponding part families in cellular manufacturing is investigated.
Journal ArticleDOI

Identification of fuzzy models of software cost estimation

TL;DR: This work presents an innovative fuzzy identification cost estimation modeling technique to deal with linguistic data, and automatically generate fuzzy membership functions and rules, and observed that the fuzzy identification model provided significantly better cost estimations than the three COCOMO models.
Journal ArticleDOI

Genetic Algorithms in Control Systems Engineering

TL;DR: The versatile and robust qualities of genetic algorithms are reviewed and their relevance for control systems engineering is highlighted.
Book

Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer

TL;DR: Parsing the Turing Test as mentioned in this paper is a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence, including whether computers and robots ever think and communicate the way humans do.
References
More filters
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

F. Rosenblatt
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.