Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

doi:10.3390/books978-3-0365-4516-5

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Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

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June 2022

362 pages

ISBN978-3-0365-4515-8 (Hardback)
ISBN978-3-0365-4516-5 (PDF)

https://doi.org/10.3390/books978-3-0365-4516-5

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This book is a reprint of the Special Issue Advances in Artificial Intelligence: Models, Optimization, and Machine Learning that was published in

Computer Science & Mathematics

Engineering

Physical Sciences

Public Health & Healthcare

Summary

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

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Keywords

large margin nearest neighbor regression; distance metrics; prototypes; evolutionary algorithm; approximate differential optimization; multiple point hill climbing; adaptive sampling; free radical polymerization; autonomous driving; object tracking; trajectory prediction; deep neural networks; stochastic methods; applied machine learning; classification and regression; data mining; ensemble model; engineering informatics; gender-based violence in Mexico; twitter messages; deep neural networks; class imbalance; k-nearest neighbor; instance-based learning; graph neural network; deep learning; hyperparameters; machine learning; optimization; inference; metaheuristics; optimization; animal-inspired; exploration; exploitation; hot rolled strip steel; deep learning; surface defects; defect classification; optimization; knockout tournament; dynamic programming algorithm; computational complexity; combinatorics; intelligent transport systems; traffic control; spatial-temporal variable speed limit; multi-agent systems; reinforcement learning; distributed W-learning; urban motorways; multi-agent framework; .NET framework; simulations; agent-based systems; agent algorithms; software design; multisensory fingerprint; interoperability; DeepFKTNet; deep learning; classification; deep learning; generative adversarial networks; image classification; transfer learning; plastic bottle; n/a