Learning and Intelligent Optimization

Learning and Intelligent Optimization
Author :
Publisher : Springer
Total Pages : 430
Release :
ISBN-10 : 3030535517
ISBN-13 : 9783030535513
Rating : 4/5 (17 Downloads)

Book Synopsis Learning and Intelligent Optimization by : Ilias S. Kotsireas

Download or read book Learning and Intelligent Optimization written by Ilias S. Kotsireas and published by Springer. This book was released on 2020-07-18 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings on Learning and Intelligent Optimization, LION 14, held in Athens, Greece, in May 2020. The 37 full papers presented together with one invited paper have been carefully reviewed and selected from 75 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components. Due to the COVID-19 pandemic, LION 14 was not held as a physical meeting.

Learning and Intelligent Optimization

Learning and Intelligent Optimization
Author :
Publisher : Springer
Total Pages : 0
Release :
ISBN-10 : 3030053474
ISBN-13 : 9783030053475
Rating : 4/5 (74 Downloads)

Book Synopsis Learning and Intelligent Optimization by : Roberto Battiti

Download or read book Learning and Intelligent Optimization written by Roberto Battiti and published by Springer. This book was released on 2019-01-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Learning and Intelligent Optimization, LION 12, held in Kalamata, Greece, in June 2018. The 28 full papers and 12 short papers presented have been carefully reviewed and selected from 62 submissions. The papers explore the advanced research developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning.

The Lion Way

The Lion Way
Author :
Publisher : Createspace Independent Publishing Platform
Total Pages : 0
Release :
ISBN-10 : 1496034023
ISBN-13 : 9781496034021
Rating : 4/5 (23 Downloads)

Book Synopsis The Lion Way by : Roberto Battiti

Download or read book The Lion Way written by Roberto Battiti and published by Createspace Independent Publishing Platform. This book was released on 2014-02-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex and dynamic problems. The LION way is about increasing the automation level and connecting data directly to decisions and actions. More power is directly in the hands of decision makers in a self-service manner, without resorting to intermediate layers of data scientists. LION is a complex array of mechanisms, like the engine in an automobile, but the user (driver) does not need to know the inner workings of the engine in order to realize its tremendous benefits. LION's adoption will create a prairie fire of innovation which will reach most businesses in the next decades. Businesses, like plants in wildfire-prone ecosystems, will survive and prosper by adapting and embracing LION techniques, or they risk being transformed from giant trees to ashes by the spreading competition.

Intelligent Computing & Optimization

Intelligent Computing & Optimization
Author :
Publisher : Springer Nature
Total Pages : 1020
Release :
ISBN-10 : 9783030932473
ISBN-13 : 3030932478
Rating : 4/5 (73 Downloads)

Book Synopsis Intelligent Computing & Optimization by : Pandian Vasant

Download or read book Intelligent Computing & Optimization written by Pandian Vasant and published by Springer Nature. This book was released on 2021-12-30 with total page 1020 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the scientific results of the fourth edition of the International Conference on Intelligent Computing and Optimization which took place at December 30–31, 2021, via ZOOM. The conference objective was to celebrate “Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization worldwide, to share knowledge, experience, innovation—marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings encloses the original and innovative scientific fields of optimization and optimal control, renewable energy and sustainability, artificial intelligence and operational research, economics and management, smart cities and rural planning, meta-heuristics and big data analytics, cyber security and blockchains, IoTs and Industry 4.0, mathematical modelling and simulation, health care and medicine.

Reactive Search and Intelligent Optimization

Reactive Search and Intelligent Optimization
Author :
Publisher : Springer Science & Business Media
Total Pages : 198
Release :
ISBN-10 : 9780387096247
ISBN-13 : 0387096248
Rating : 4/5 (47 Downloads)

Book Synopsis Reactive Search and Intelligent Optimization by : Roberto Battiti

Download or read book Reactive Search and Intelligent Optimization written by Roberto Battiti and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics. Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities for the automated tuning of these parameters.

Optimization in Machine Learning and Applications

Optimization in Machine Learning and Applications
Author :
Publisher : Springer Nature
Total Pages : 202
Release :
ISBN-10 : 9789811509940
ISBN-13 : 9811509948
Rating : 4/5 (40 Downloads)

Book Synopsis Optimization in Machine Learning and Applications by : Anand J. Kulkarni

Download or read book Optimization in Machine Learning and Applications written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2019-11-29 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.

Advances in Learning Automata and Intelligent Optimization

Advances in Learning Automata and Intelligent Optimization
Author :
Publisher : Springer Nature
Total Pages : 340
Release :
ISBN-10 : 9783030762919
ISBN-13 : 3030762912
Rating : 4/5 (19 Downloads)

Book Synopsis Advances in Learning Automata and Intelligent Optimization by : Javidan Kazemi Kordestani

Download or read book Advances in Learning Automata and Intelligent Optimization written by Javidan Kazemi Kordestani and published by Springer Nature. This book was released on 2021-06-23 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits • Presents the latest advances in learning automata-based optimization approaches. • Addresses the memetic models of learning automata for solving NP-hard problems. • Discusses the application of learning automata for behavior control in evolutionary computation in detail. • Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.