Genetic Algorithms In Elixir
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| Author | : Sean Moriarity |
| Publisher | : Pragmatic Bookshelf |
| Total Pages | : 304 |
| Release | : 2021-01-20 |
| Genre | : Computers |
| ISBN | : 168050830X |
From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you'll learn the underlying principles of problem solving using genetic algorithms. Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind. Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications. Open your eyes to a unique and powerful field - without having to learn a new language or framework. What You Need: You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.
| Author | : Frances Buontempo |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2019 |
| Genre | : Artificial intelligence |
| ISBN | : 9781680506204 |
Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to machine learning. Discover machine learning algorithms using a handful of self-contained recipes. Create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, and cellular automata. Find minima and maxima, using hill climbing and simulated annealing. Try selection mathods, including tournament and roulette wheels. Learn about heuristics, fitness functions, metrics, and clusters.
| Author | : David Edward Goldberg |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 436 |
| Release | : 1989 |
| Genre | : Computers |
| ISBN | : |
A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.
| Author | : Gene I. Sher |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 836 |
| Release | : 2012-11-06 |
| Genre | : Computers |
| ISBN | : 1461444632 |
Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang. With a foreword written by Joe Armstrong, this handbook offers an extensive tutorial for creating a state of the art Topology and Weight Evolving Artificial Neural Network (TWEANN) platform. In a step-by-step format, the reader is guided from a single simulated neuron to a complete system. By following these steps, the reader will be able to use novel technology to build a TWEANN system, which can be applied to Artificial Life simulation, and Forex trading. Because of Erlang’s architecture, it perfectly matches that of evolutionary and neurocomptational systems. As a programming language, it is a concurrent, message passing paradigm which allows the developers to make full use of the multi-core & multi-cpu systems. Handbook of Neuroevolution Through Erlang explains how to leverage Erlang’s features in the field of machine learning, and the system’s real world applications, ranging from algorithmic financial trading to artificial life and robotics.
| Author | : Kevin Kelly |
| Publisher | : Basic Books |
| Total Pages | : 666 |
| Release | : 2009-04-30 |
| Genre | : Science |
| ISBN | : 078674703X |
Out of Control chronicles the dawn of a new era in which the machines and systems that drive our economy are so complex and autonomous as to be indistinguishable from living things.
| Author | : Jonas Peters |
| Publisher | : MIT Press |
| Total Pages | : 289 |
| Release | : 2017-11-29 |
| Genre | : Computers |
| ISBN | : 0262037319 |
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.
| Author | : Jagdish Chand Bansal |
| Publisher | : Springer |
| Total Pages | : 194 |
| Release | : 2018-06-06 |
| Genre | : Technology & Engineering |
| ISBN | : 3319913417 |
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
| Author | : Sean Moriarity |
| Publisher | : Pragmatic Bookshelf |
| Total Pages | : 244 |
| Release | : 2021-02-09 |
| Genre | : Computers |
| ISBN | : 9781680507942 |
From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you'll learn the underlying principles of problem solving using genetic algorithms. Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind. Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications. Open your eyes to a unique and powerful field - without having to learn a new language or framework. What You Need: You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.
| Author | : Britta Folmer |
| Publisher | : Academic Press |
| Total Pages | : 558 |
| Release | : 2016-12-16 |
| Genre | : Technology & Engineering |
| ISBN | : 0128035587 |
The Craft and Science of Coffee follows the coffee plant from its origins in East Africa to its current role as a global product that influences millions of lives though sustainable development, economics, and consumer desire.For most, coffee is a beloved beverage. However, for some it is also an object of scientifically study, and for others it is approached as a craft, both building on skills and experience. By combining the research and insights of the scientific community and expertise of the crafts people, this unique book brings readers into a sustained and inclusive conversation, one where academic and industrial thought leaders, coffee farmers, and baristas are quoted, each informing and enriching each other.This unusual approach guides the reader on a journey from coffee farmer to roaster, market analyst to barista, in a style that is both rigorous and experience based, universally relevant and personally engaging. From on-farming processes to consumer benefits, the reader is given a deeper appreciation and understanding of coffee's complexity and is invited to form their own educated opinions on the ever changing situation, including potential routes to further shape the coffee future in a responsible manner. - Presents a novel synthesis of coffee research and real-world experience that aids understanding, appreciation, and potential action - Includes contributions from a multitude of experts who address complex subjects with a conversational approach - Provides expert discourse on the coffee calue chain, from agricultural and production practices, sustainability, post-harvest processing, and quality aspects to the economic analysis of the consumer value proposition - Engages with the key challenges of future coffee production and potential solutions
| Author | : Jim Blandy |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 646 |
| Release | : 2017-11-21 |
| Genre | : Computers |
| ISBN | : 1491927232 |
Rust is a new systems programming language that combines the performance and low-level control of C and C++ with memory safety and thread safety. Rust’s modern, flexible types ensure your program is free of null pointer dereferences, double frees, dangling pointers, and similar bugs, all at compile time, without runtime overhead. In multi-threaded code, Rust catches data races at compile time, making concurrency much easier to use. Written by two experienced systems programmers, this book explains how Rust manages to bridge the gap between performance and safety, and how you can take advantage of it. Topics include: How Rust represents values in memory (with diagrams) Complete explanations of ownership, moves, borrows, and lifetimes Cargo, rustdoc, unit tests, and how to publish your code on crates.io, Rust’s public package repository High-level features like generic code, closures, collections, and iterators that make Rust productive and flexible Concurrency in Rust: threads, mutexes, channels, and atomics, all much safer to use than in C or C++ Unsafe code, and how to preserve the integrity of ordinary code that uses it Extended examples illustrating how pieces of the language fit together
