Evolutionary Multi-Task Optimization [E-Book] : Foundations and Methodologies / by Liang Feng, Abhishek Gupta, Kay Chen Tan, Yew Soon Ong.
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 induc...
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Full text |
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Personal Name(s): | Feng, Liang, author |
Gupta, Abhishek, author / Ong, Yew Soon, author / Tan, Kay Chen, author | |
Edition: |
1st edition 2023. |
Imprint: |
Singapore :
Springer,
2023
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Physical Description: |
X, 219 pages 1 illustration (online resource) |
Note: |
englisch |
ISBN: |
9789811956508 |
DOI: |
10.1007/978-981-19-5650-8 |
Series Title: |
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Machine Learning: Foundations, Methodologies, and Applications
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Subject (LOC): |
- Chapter 1.Introduction
- Chapter 2. Overview and Application-driven Motivations of Evolutionary Multitasking
- Chapter 3.The Multi-factorial Evolutionary Algorithm
- Chapter 4. Multi-factorial Evolutionary Algorithm with Adaptive Knowledge Transfer
- Chapter 5.Explicit Evolutionary Multi-task Optimization Algorithm
- Chapter 6.Evolutionary Multi-task Optimization for Generalized Vehicle Routing Problem With Occasional Drivers
- Chapter 7. Explicit Evolutionary Multi-task Optimization for Capacitated Vehicle Routing Problem
- Chapter 8. Multi-Space Evolutionary Search for Large Scale Single-Objective Optimization
- Chapter 9.Multi-Space Evolutionary Search for Large-scale Multi-Objective Optimization.