This book is a collection of chapters on the state of art in the area of intelligent machines. This research provides a sound basis to make autonomous systems human-like. The contributions include an introduction to intelligent machines; supervisory control of multiple UAVs; and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; dynamic path planning; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.

System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex systems which are intelligent and robust.

The book includes a sample of research on the innovative applications of advanced computational intelligence paradigms. The characteristics of computational intelligence paradigms such as learning, generalization based on learned knowledge, knowledge extraction from imprecise and incomplete data are the extremely important for the implementation of intelligent machines. The chapters include architectures of computational intelligence paradigms, knowledge discovery, pattern classification, clusters, support vector machines and gene linkage analysis. We believe that the research on computational intelligence will simulate great interest among designers and researchers of complex systems. It is important to use the fusion of various constituents of computational intelligence to offset the demerits of one paradigm by the merits of another.

This book presents the most recent advances in fuzzy clustering techniques and their applications. The contents include Introduction to Fuzzy Clustering; Fuzzy Clustering based Principal Component Analysis; Fuzzy Clustering based Regression Analysis; Kernel based Fuzzy Clustering; Evaluation of Fuzzy Clustering; Self-Organized Fuzzy Clustering. This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.

System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex systems which are intelligent and robust. The book includes a sample of research on the innovative applications of advanced computational intelligence paradigms. The characteristics of computational intelligence paradigms such as learning, generalization based on learned knowledge, knowledge extraction from imprecise and incomplete data are the extremely important for the implementation of intelligent machines. The chapters include architectures of computational intelligence paradigms, knowledge discovery, pattern classification, clusters, support vector machines and gene linkage analysis. We believe that the research on computational intelligence will simulate great interest among designers and researchers of complex systems. It is important to use the fusion of various constituents of computational intelligence to offset the demerits of one paradigm by the merits of another.

This book is a collection of chapters on the state of art in the area of intelligent machines. This research provides a sound basis to make autonomous systems human-like. The contributions include an introduction to intelligent machines; supervisory control of multiple UAVs; and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; dynamic path planning; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.

This book presents the most recent advances in fuzzy clustering techniques and their applications. The contents include Introduction to Fuzzy Clustering; Fuzzy Clustering based Principal Component Analysis; Fuzzy Clustering based Regression Analysis; Kernel based Fuzzy Clustering; Evaluation of Fuzzy Clustering; Self-Organized Fuzzy Clustering. This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.