Handbook on Computer Learning and Intelligence

Volume 1: Explainable AI and Supervised Learning
	Preface
	About the Editor
	Acknowledgments
	Contents
	Introduction
	Part I: Explainable AI
		1. Explainable Artificial Intelligence and Computational Intelligence: Past and Present • Mojtaba Yeganejou and Scott Dick
		2. Fundamentals of Fuzzy Set Theory • Fernando Gomide
		3. Granular Computing • Andrzej Bargiela and Witold Pedrycz
		4. Evolving Fuzzy and Neuro-Fuzzy Systems: Fundamentals, Stability, Explainability, Useability, and Applications • Edwin Lughofer
		5. Incremental Fuzzy Machine Learning for Online Classification of Emotions in Games from EEG Data Streams • Daniel Leite, Volnei Frigeri Jr., and Rodrigo Medeiros
		6. Causal Inference in Medicine and in Health Policy: A Summary • Wenhao Zhang, Ramin Ramezani, and Arash Naeim
	Part II: Supervised Learning
		7. Fuzzy Classifiers • Hamid Bouchachia
		8. Kernel Models and Support Vector Machines • Denis Kolev, Mikhail Suvorov, and Dmitry Kangin
		9. Evolving Connectionist Systems for Adaptive Learning and Knowledge Discovery: From Neuro-Fuzzy to Spiking, Neurogenetic, and Quantum Inspired: A Review of Principles and Applications • Nikola Kirilov Kasabov
		10. Supervised Learning Using Spiking Neural Networks • Abeegithan Jeyasothy, Shirin Dora, Suresh Sundaram, and Narasimhan Sundararajan
		11. Fault Detection and Diagnosis Based on an LSTM Neural Network Applied to a Level Control Pilot Plant • Emerson Vilar de Oliveira, Yuri Thomas Nunes, Mailson Ribeiro Santos, and Luiz Affonso Guedes
		12. Conversational Agents: Theory and Applications • Mattias Wahde and Marco Virgolin
	Index
Volume 2: Deep Learning, Intelligent Control and Evolutionary Computation
	Preface
	About the Editor
	Acknowledgments
	Contents
	Introduction
	Part III: Deep Learning
		13. Deep Learning and Its Adversarial Robustness: A Brief Introduction • Fu Wang, Chi Zhang, Peipei Xu, and Wenjie Ruan
		14. Deep Learning for Graph-Structured Data • Luca Pasa, Nicolò Navarin, and Alessandro Sperduti
		15. A Critical Appraisal on Deep Neural Networks: Bridge the Gap between Deep Learning and Neuroscience via XAI • Anna-Sophie Bartle, Ziping Jiang, Richard Jiang, Ahmed Bouridane, and Somaya Almaadeed
		16. Ensemble Learning • Y. Liu and Q. Zhao
		17. A Multistream Deep Rule-Based Ensemble System for Aerial Image Scene Classification • Xiaowei Gu and Plamen P. Angelov
	Part IV: Intelligent Control
		18. Fuzzy Model-Based Control: Predictive and Adaptive Approach • Igor Škrjanc and Sašo Blažič
		19. Reinforcement Learning with Applications in Autonomous Control and Game Theory • Kyriakos G. Vamvoudakis, Frank L. Lewis, and Draguna Vrabie
		20. Nature-Inspired Optimal Tuning of Fuzzy Controllers • Radu-Emil Precup and Radu-Codrut David
		21. Indirect Self-evolving Fuzzy Control Approaches and Their Applications • Zhao-Xu Yang and Hai-Jun Rong
	Part V: Evolutionary Computation
		22. Evolutionary Computation: Historical View and Basic Concepts • Carlos A. Coello Coello, Carlos Segura, and Gara Miranda
		23. An Empirical Study of Algorithmic Bias • Dipankar Dasgupta and Sajib Sen
		24. Collective Intelligence: A Comprehensive Review of Metaheuristic Algorithms Inspired by Animals • Fevrier Valdez
		25. Fuzzy Dynamic Parameter Adaptation for Gray Wolf Optimization of Modular Granular Neural Networks Applied to Human Recognition Using the Iris Biometric Measure • Patricia Melin, Daniela Sánchez, and Oscar Castillo
		26. Evaluating Inter-Task Similarity for Multifactorial Evolutionary Algorithm from Different Perspectives • Lei Zhou, Liang Feng, Min Jiang, and Kay Chen Tan
	Index