This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

A valuable reference and a rich source of exercises with sample solutions, this book will be useful to both students and lecturers. Its original concept makes it particularly suitable for self-study.

This book presents a history of differential equations, both ordinary and partial, as well as the calculus of variations, from the origins of the subjects to around 1900.

This book for self-study provides a detailed treatment of conditional expectation and probability, a topic that in principle belongs to probability theory, but is essential as a tool for stochastic processes.

This book brings together all of the important new results on the state space framework for exponential smoothing.

In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject. This book describes how neural networks operate from the mathematical point of view.

The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest.

With its many beautiful colour pictures, this book gives fascinating insights into the unusual forms and behaviour of matter under extremely high pressures and temperatures.

This material helps the reader in several ways, for example: by giving a synopsis of the book, by explaining where the various data tables are and what they deal with, by telling what theory is described where.

The book can be adopted as the main textbook for courses on intelligent agents, advanced topics in AI or contemporary AI technologies; application developers can use it as a complete technical guide and reference manual for the iJADK ...