Dynamic Fuzzy Machine Learning

This book develops a self-contained framework for machine learning based on dynamic fuzzy model via elabrating on concepts and algorithms. It further explains mechanisms for agent learning and agent ubiquitous learning, and discusses design of Bayesian quantum stochastic learning for various environments. Demonstrating theories with practical examples, the book is of interests to computer scientists and engineers on artificial intelligence.

Table of Contents

Chapter 1 Dynamic Fuzzy Machine Learning Model
Chapter 2 Dynamic Fuzzy Autonomic Learning Subspace Algorithm
Chapter 3 Dynamic Fuzzy Decision Tree Learning
Chapter 4 Concept Learning Based On Dynamic Fuzzy Sets
Chapter 5 Semi-Supervised Multi-Task Learning Based On Dynamic Fuzzy Sets
Chapter 6 Dynamic Fuzzy Hierarchical Relationships
Chapter 7 Multi-Agent Learning Model Based On Dynamic Fuzzy Logic