Cover of An Introduction to Genetic Algorithms

An Introduction to Genetic Algorithms

"This is the best general book on Genetic Algorithms written to date. It covers background, history, and motivation; it selects important, informative examples of applications and discusses the use of Genetic Algorithms in scientific models; and it gives a good account of the status of the theory of Genetic Algorithms. Best of all the book presents its material in clear, straightforward, felicitous prose, accessible to anyone with a college-level scientific background. If you want a broad, solid understanding of Genetic Algorithms — where they came from, what's being done with them, and where they are going — this is the book.

Read more

— John H. Holland, Professor, Computer Science and Engineering, and Professor of Psychology, The University of Michigan; External Professor, the Santa Fe Institute. Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics — particularly in machine learning, scientific modeling, and artificial life — and reviews a broad span of research, including the work of Mitchell and her colleagues.

Audience
adult
Length
medium · 205 pages

Click a tag to see books like this one that share it. Point at it (on a phone, tap it) for less of it instead.

Read it? Sign in to help tag it.

Liked An Introduction to Genetic Algorithms? Here’s where I’d start.

These suit anyone who liked An Introduction to Genetic Algorithms. Sign in and mark a few books for picks shaped around your own taste.

  1. Selected Papers on Computer Science Shares computer science, programming, science
  2. Information Theory, Inference and Learning Algorithms Shares computer science, machine learning, science
  3. The Computational Beauty of Nature - Computer Explorations of Fractals, Chaos, Complex Systems & Adaption (Paper) (Bradford Books) Shares computer science, programming, science
  4. Artificial Life: A Report from the Frontier Where Computers Meet Biology Shares science, computer science, nonfiction

“People who read An Introduction to Genetic Algorithms tend to reach for these next.”

  1. Wetware: A Computer in Every Living Cell
  2. Artificial Intelligence: A Modern Approach
  3. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
  4. Artificial Intelligence for Games (The Morgan Kaufmann Series in Interactive 3D Technology)

“If you want more of the same (science about artificial intelligence), start with these.”

  1. All of Statistics: A Concise Course in Statistical Inference
  2. Newton's Clock: Chaos in the Solar System
  3. A First Course in String Theory
  4. Abstract Algebra

“If it was the computer science that hooked you, try one of these.”

  1. Data Structures Using C and C++
  2. Introduction to the Theory of Computation
  3. The Annotated Turing: A Guided Tour Through Alan Turing's Historic Paper on Computability and the Turing Machine
  4. Types and Programming Languages

“These start from a similar idea, even if they go somewhere else with it.”

  1. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
  2. Think Complexity: Complexity Science and Computational Modeling
  3. Algorithm Design
  4. Combinatorial Optimization: Algorithms and Complexity