h1. Clever Algorithms: Nature-Inspired Programming Recipes

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"Read Online":https://cleveralgorithms.com/nature-inspired/index.html | "Amazon":https://amzn.to/4iKM9uc | "GoodReads":https://www.goodreads.com/book/show/10321060-clever-algorithms | "Google Books":https://www.google.com.au/books/edition/Clever_Algorithms/SESWXQphCUkC | "Download PDF":https://raw.githubusercontent.com/Jason2Brownlee/CleverAlgorithms/master/release/clever_algorithms.pdf ("code":https://raw.githubusercontent.com/Jason2Brownlee/CleverAlgorithms/master/release/clever_algorithms-src.zip)

h2. Overview

Clever Algorithms: Nature-Inspired Programming Recipes is an open source book that describes a large number of algorithmic techniques from the the fields of Biologically Inspired Computation, Computational Intelligence and Metaheuristics in a complete, consistent, and centralized manner such that they are accessible, usable, and understandable. This is a repository for the book project.

h3. Book Details

h3. Blurb

bq. Implementing an Artificial Intelligence algorithm is difficult. Algorithm descriptions may be incomplete, inconsistent, and distributed across a number of papers, chapters and even websites. This can result in varied interpretations of algorithms, undue attrition of algorithms, and ultimately bad science. This book is an effort to address these issues by providing a handbook of algorithmic recipes drawn from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence, described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

h3. Table of Contents

Background

Introduction

Algorithms

Stochastic Algorithms

Random Search

Adaptive Random Search

Stochastic Hill Climbing

Iterated Local Search

Guided Local Search

Variable Neighborhood Search

Greedy Randomized Adaptive Search

Scatter Search

Tabu Search

Reactive Tabu Search

Evolutionary Algorithms

Genetic Algorithm

Genetic Programming

Evolution Strategies

Differential Evolution

Evolutionary Programming

Grammatical Evolution

Gene Expression Programming

Learning Classifier System

Non-dominated Sorting Genetic Algorithm

Strength Pareto Evolutionary Algorithm

Physical Algorithms

Simulated Annealing

Extremal Optimization

Harmony Search

Cultural Algorithm

Memetic Algorithm

Probabilistic Algorithms

Population-Based Incremental Learning

Univariate Marginal Distribution Algorithm

Compact Genetic Algorithm

Bayesian Optimization Algorithm

Cross-Entropy Method

Swarm Algorithms

Particle Swarm Optimization

Ant System

Ant Colony System

Bees Algorithm

Bacterial Foraging Optimization Algorithm

Immune Algorithms

Clonal Selection Algorithm

Negative Selection Algorithm

Artificial Immune Recognition System

Immune Network Algorithm

Dendritic Cell Algorithm

Neural Algorithms

Perceptron

Back-propagation

Hopfield Network

Learning Vector Quantization

Self-Organizing Map

Extensions

Advanced Topics

Programming Paradigms

Devising New Algorithms

Testing Algorithms

Visualizing Algorithms

Problem Solving Strategies

Benchmarking Algorithms

Appendix A - Ruby: Quick-Start Guide

h2. Project

h3. How to Build

Assumes a POSIX workstation with LaTex installed.

<code>git clone https://github.com/Jason2Brownlee/CleverAlgorithms.git</code>

@cd CleverAlgorithms@

@make dist@

h2. License

(c) Copyright 2011-2024 Jason Brownlee. Some Rights Reserved. This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/2.5/au/">Creative Commons Attribution-Noncommercial-Share Alike 2.5 Australia License</a>. <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/2.5/au/"> <img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-sa/2.5/au/88x31.png" /> </a>

CleverAlgorithms

Install / Use

README