PART I FUNDAMENTALS -- Introduction -- Decisions -- Evolution of Decision Support Systems -- PART II INTELLIGENT DECISION SUPPORT SYSTEMS -- Intelligent Decision Support Systems (IDSS) -- Model-driven Intelligent Decision Support -- Data-driven Intelligent Decision Support -- The use of Intelligent Models in Decision Support -- PART III DEVELOPMENT AND APPLICATION OF IDSS -- Tools for IDSS Development -- Advanced IDSS Topics and Applications -- Summary, Open Challenges and Concluding Remarks.

This book presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems.