{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":36,"n_cols":5,"rows_kept":36,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[10,2,10,3],[11,2,11,3],[13,2,13,3],[13,4,13,5],[14,2,14,3],[14,4,14,5],[15,2,15,3],[15,4,15,5],[16,2,16,3],[18,2,18,3],[22,2,22,3],[23,2,23,3],[24,2,24,3],[25,2,25,3],[28,2,28,3],[29,2,29,3],[32,2,32,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910466938503321"]
[null,null,"Titolo",null,"Dental anatomy"]
[null,null,"Pubbl/distr/stampa",null,"[Place of publication not identified] : , : BarCharts, Inc., , [2016]"]
[null,null,"ISBN",null,"1-4232-3374-3"]
[null,null,"Descrizione fisica",null,"1 online resource (6 pages)"]
[null,null,"Collana",null,"Quick Study Academic"]
[null,null,"Disciplina",null,"611.31"]
[null,null,"Soggetti",null,"Mouth - Anatomy"]
[{"$nulls":4},"Teeth - Anatomy"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9911008398403321"]
[null,null,"Autore",null,"Moriarity Sean"]
[null,null,"Titolo",null,"Genetic algorithms in Elixir : solve problems using evolution / / Sean Moriarity"]
[null,null,"Pubbl/distr/stampa",null,"[Raleigh, North Carolina] : , : The Pragmatic Programmers, LLC, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"9781680508307"]
[{"$nulls":4},"168050830X"]
[{"$nulls":4},"9781680508314"]
[{"$nulls":4},"1680508318"]
[null,null,"Edizione",null,"[First edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (235 pages)"]
[null,null,"Disciplina",null,"518.1"]
[null,null,"Soggetti",null,"Algorithms"]
[{"$nulls":4},"Evolutionary programming (Computer science)"]
[{"$nulls":4},"Genetic algorithms"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Cover -- Table of Contents -- Disclaimer -- Acknowledgments -- Preface -- Who This Book Is For -- What's in This Book -- How to Use This Book -- How Does Elixir Fit In? -- 1. Writing Your First Genetic Algorithm -- Understanding Genetic Algorithms -- Introducing the One-Max Problem -- Initializing the Population -- Understanding the Flow of Genetic Algorithms -- Selecting Parents -- Creating Children -- Running Your Solution -- Adding Mutation -- What You Learned -- 2. Breaking Down Genetic Algorithms -- Reviewing Genetic Algorithms -- Looking Deeper into Genetic Algorithms -- Using Mix to Write Genetic Algorithms -- Building a Framework for Genetic Algorithms -- Understanding Hyperparameters -- Solving the One-Max Problem Again -- What You Learned -- 3. Encoding Problems and Solutions -- Using Structs to Represent Chromosomes -- Using Behaviours to Model Problems -- Understanding and Choosing Genotypes -- Solving One-Max for the Last Time -- Spelling Words with Genetic Algorithms -- What You Learned -- 4. Evaluating Solutions and Populations -- Optimizing Cargo Loads -- Introducing Penalty Functions -- Applying a Penalty to the Shipping Problem -- Defining Termination Criteria -- Applying Termination Criteria to Shipping -- Crafting Fitness Functions -- Exploring Different Types of Optimization -- What You Learned -- "]
[{"$nulls":4},"5. Selecting the Best -- Exploring Selection -- Customizing Selection in Your Framework -- Implementing Common Selection Strategies -- What You Learned -- 6. Generating New Solutions -- Introducing N-Queens -- Solving N-Queens with Order-One Crossover -- Exploring Crossover -- Implementing Other Common Crossover Strategies -- Crossing Over More Than Two Parents -- Implementing Chromosome Repairment -- What You Learned -- 7. Preventing Premature Convergence -- Breaking Codes with Genetic Algorithms -- Understanding Mutation."]
[{"$nulls":4},"Customizing Mutation in Your Framework -- Implementing Common Mutation Strategies -- Other Methods to Combat Convergence -- What You Learned -- 8. Replacing and Transitioning -- Creating a Class Schedule -- Understanding Reinsertion -- Experimenting with Reinsertion -- Growing and Shrinking Populations -- Local Versus Global Reinsertion -- What You Learned -- 9. Tracking Genetic Algorithms -- Using Genetic Algorithms to Simulate Evolution -- Logging Statistics Using ETS -- Tracking Genealogy in a Genealogy Tree -- What You Learned -- 10. Visualizing the Results -- Visualizing the Genealogy of the Tiger Evolution -- Visualizing Basic Statistics -- Playing Tetris with Genetic Algorithms -- Installing and Compiling ALEx -- What You Learned -- 11. Optimizing Your Algorithms -- Benchmarking and Profiling Genetic Algorithms -- Writing Fast Elixir -- Improving Performance with Parallelization -- Improving Performance with NIFs -- What You Learned -- 12. Writing Tests and Code Quality -- Understanding Randomness -- Writing Property Tests with ExUnit -- Cleaning Up Your Framework -- Writing Type Specifications -- What You Learned -- 13. Moving Forward -- Learning with Evolution -- Designing with Evolution -- Trading with Evolution -- Networking with Evolution -- Evolving Neural Networks -- Where to Go Next -- Bibliography -- Index -- - SYMBOLS - -- - A - -- - B - -- - C - -- - D - -- - E - -- - F - -- - G - -- - H - -- - I - -- - J - -- - K - -- - L - -- - M - -- - N - -- - O - -- - P - -- - Q - -- - R - -- - S - -- - T - -- - U - -- - V - -- - W - -- - X - -- - Z -."]
[null,null,null,"Sommario/riassunto","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."]