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Complex behavior in evolutionary robotics /
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| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boston :
De Gruyter,
[2015]
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a König, Lukas, |e author. | |
| 245 | 1 | 0 | |a Complex behavior in evolutionary robotics / |c Lukas König. |
| 264 | 1 | |a Boston : |b De Gruyter, |c [2015] | |
| 264 | 4 | |c ©2015 | |
| 300 | |a 1 online resource (262 pages) : |b illlustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Acknowledgements; Contents; List of Figures; List of Tables; List of Notations; 1 Introduction; 1.1 Evolutionary Robotics and Evolutionary Swarm Robotics; 1.2 Further Classifications; 1.3 Challenges of ER; 1.4 Structure and Major Contributions of the Thesis; 2 Robotics, Evolution and Simulation; 2.1 Evolutionary Training of Robot Controllers; 2.1.1 Two Views on Selection in ER and ESR; 2.1.2 Classification of Fitness Functions in ER; 2.1.3 The Bootstrap Problem; 2.1.4 The Reality Gap; 2.1.5 Decentralized Online Evolution in ESR. | |
| 505 | 8 | |a 2.1.6 Evolvability, Controller Representation and the Genotype-Phenotype Mapping2.1.7 Controller Representation; 2.1.8 Recombination Operators; 2.1.9 Success Prediction in ESR; 2.2 Agent-based Simulation; 3 The Easy Agent Simulation; 3.1 History of the Easy Agent Simulation Framework; 3.2 Basic Idea and Architectural Concept; 3.2.1 Overview; 3.2.2 Preliminaries; 3.2.3 Classification of the Architecture; 3.2.4 The SPI Architecture from an MVC Perspective; 3.2.5 Comparison of the SPI Architecture with State-of-the-Art ABS Frameworks; 3.3 Implementation of the SPI within the EAS Framework. | |
| 505 | 8 | |a 3.3.1 Overview3.3.2 Plugins; 3.3.3 Master Schedulers; 3.3.4 The classes SimulationTime and Wink; 3.3.5 The Interface EASRunnable; 3.3.6 "Everything is an Agent": a Philosophical Decision; 3.3.7 Running a Simulation; 3.3.8 Getting Started; 3.4 A Comparative Study and Evaluation of the EAS Framework; 3.4.1 Method of Experimentation; 3.4.2 Results and Discussion; 3.5 Chapter Résumé; 4 Evolution Using Finite State Machines; 4.1 Theoretical Foundations; 4.1.1 Preliminaries; 4.1.2 Definition of the MARB Controller Model; 4.1.3 Encoding MARBs; 4.1.4 Mutation and Hardening. | |
| 505 | 8 | |a 4.1.5 Selection and Recombination4.1.6 Fitness calculation; 4.1.7 The Memory Genome: a Decentralized Elitist Strategy; 4.1.8 Fitness Adjustment after Mutation, Recombination and Reactivation of the Memory Genome; 4.1.9 The Robot Platforms; 4.2 Preliminary Parameter Adjustment using the Example of Collision Avoidance; 4.2.1 Specification of Evolutionary Parameters; 4.2.2 Method of Experimentation; 4.2.3 Evaluation and Discussion; 4.2.4 Concluding Remarks; 4.3 A Comprehensive Study Using the Examples of Collision Avoidance and Gate Passing; 4.3.1 Method of Experimentation. | |
| 505 | 8 | |a 4.3.2 Experimental results4.3.3 Concluding remarks; 4.4 Experiments With Real Robots; 4.4.1 Evolutionary Model; 4.4.2 Method of Experimentation; 4.4.3 Results and Discussion; 4.4.4 Concluding Remarks; 4.5 Chapter Résumé; 5 Evolution and the Genotype-Phenotype Mapping; 5.1 Overview of the Presented Approach; 5.2 A Completely Evolvable Genotype-Phenotype Mapping; 5.2.1 Definition of (complete) evolvability; 5.2.2 Properties of ceGPM-based genotypic encodings; 5.2.3 The Translator Model MAPT and the Course of Evolution; 5.2.4 Genotypic and Phenotypic Spaces; 5.2.5 Evolutionary Operators. | |
| 520 | |a <!Doctype html public ""-//w3c//dtd html 4.0 transitional//en""> <html><head> <meta content=""text/html; charset=iso-8859-1"" http-equiv=content-type> <meta name=generator content=""mshtml 8.00.6001.23627""></head> <body> This book examines four new approaches for problem solving in evolutionary robotics and agent simulation. Of particular interest is a new method that imitates natural evolution, allowing mutation and recombination operations to be adapted during the robotic evolution process. </body></html> | ||
| 546 | |a In English. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Evolutionary robotics. | |
| 650 | 6 | |a Robotique évolutive. | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Engineering (General) |2 bisacsh | |
| 650 | 7 | |a Evolutionary robotics. |2 fast |0 (OCoLC)fst00917349 | |
| 776 | 0 | 8 | |i Print version: |a König, Lukas. |t Complex behavior in evolutionary robotics. |d Boston : De Gruyter, [2015] |h xx, 242 pages |z 9783110408546 |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=984276 |z Texto completo |
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