Evolutionary Multi Task Optimization
DOWNLOAD
Download Evolutionary Multi Task Optimization PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Evolutionary Multi Task Optimization book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Evolutionary Multi Task Optimization
DOWNLOAD
Author : Liang Feng
language : en
Publisher: Springer
Release Date : 2022-11-28
Evolutionary Multi Task Optimization written by Liang Feng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-28 with Computers categories.
A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems, each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.
Evolutionary Multi Task Optimization
DOWNLOAD
Author : Liang Feng
language : en
Publisher: Springer Nature
Release Date : 2023-03-29
Evolutionary Multi Task Optimization written by Liang Feng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Computers categories.
A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems, each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.
Evolutionary Multi Criterion Optimization
DOWNLOAD
Author : Hisao Ishibuchi
language : en
Publisher: Springer Nature
Release Date : 2021-03-24
Evolutionary Multi Criterion Optimization written by Hisao Ishibuchi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-24 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021 held in Shenzhen, China, in March 2021. The 47 full papers and 14 short papers were carefully reviewed and selected from 120 submissions. The papers are divided into the following topical sections: theory; algorithms; dynamic multi-objective optimization; constrained multi-objective optimization; multi-modal optimization; many-objective optimization; performance evaluations and empirical studies; EMO and machine learning; surrogate modeling and expensive optimization; MCDM and interactive EMO; and applications.
Recent Advances In Evolutionary Multi Objective Optimization
DOWNLOAD
Author : Slim Bechikh
language : en
Publisher: Springer
Release Date : 2016-08-09
Recent Advances In Evolutionary Multi Objective Optimization written by Slim Bechikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-09 with Technology & Engineering categories.
This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.
Bio Inspired Computing Theories And Applications
DOWNLOAD
Author : Linqiang Pan
language : en
Publisher: Springer Nature
Release Date : 2024-04-15
Bio Inspired Computing Theories And Applications written by Linqiang Pan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.
The two-volume set CCIS 2061 and 2062 constitutes the refereed post-conference proceedings of the 18th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2023, held in Changsha, China, during December 15–17, 2023. The 64 revised full papers presented in these proceedings were carefully reviewed and selected from 168 submissions. The papers are organized in the following topical sections: Volume I: Evolutionary Computation and Swarm Intelligence; and Membrane Computing and DNA Computing Volume II: Machine Learning and Applications; and Intelligent Control and Application.
Cognitive Multitasking Towards Augmented Intelligence
DOWNLOAD
Author : Yew Soon Ong
language : en
Publisher: Frontiers Media SA
Release Date : 2021-03-04
Cognitive Multitasking Towards Augmented Intelligence written by Yew Soon Ong and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-04 with Science categories.
Simulated Evolution And Learning
DOWNLOAD
Author : Yuhui Shi
language : en
Publisher: Springer
Release Date : 2017-11-01
Simulated Evolution And Learning written by Yuhui Shi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-01 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.
Advanced Intelligent Computing Technology And Applications
DOWNLOAD
Author : De-Shuang Huang
language : en
Publisher: Springer Nature
Release Date : 2025-07-25
Advanced Intelligent Computing Technology And Applications written by De-Shuang Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Computers categories.
The 20-volume set LNCS 15842-15861, together with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The 1206 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. They deal with emerging and challenging topics in artificial intelligence, machine learning, pattern recognition, bioinformatics, and computational biology.
Advances In Swarm Intelligence
DOWNLOAD
Author : Ying Tan
language : en
Publisher: Springer Nature
Release Date : 2023-07-07
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-07 with Computers categories.
This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence”. The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization.
Genetic Programming
DOWNLOAD
Author : Eric Medvet
language : en
Publisher: Springer Nature
Release Date : 2022-04-19
Genetic Programming written by Eric Medvet and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-19 with Computers categories.
This book constitutes the refereed proceedings of the 25th European Conference on Genetic Programming, EuroGP 2022, held as part of Evo*2021, as Virtual Event, in April 2022, co-located with the Evo*2022 events, EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 35 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover topics including developing new operators for variants of GP algorithms, as well as exploring GP applications to the optimization of machine learning methods and the evolution of complex combinational logic circuits.