Intelligent Decision Support Systems - Hardcover

Sąnchez-Marrč, Miquel

Hardcover

ISBN 10: 3030877892 ISBN 13: 9783030877897

Publisher: Springer, 2022

Synopsis

This book, with invaluable contributions of Professor Franz Wotawa in chapters 5 and 7, 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.

About this title

About the Author

Miquel Sąnchez-Marrč received a B.Sc. in Computer Science in 1988 and a M.Sc. in Computer Science in 1991 both from Barcelona School of Informatics (FIB), and a Ph.D. in Computer Science from Universitat Politčcnica de Catalunya (UPC) in 1996. He is an Associate Professor in the Computer Science (CS) Dept. of UPC since 1997 (tenure). He is member of the Intelligent Data Science and Artificial Intelligence Research Centre (IDEAI-UPC). He received an Accesit of the Oms i De Prat 1991 Prize, for his Master's Thesis. He co-founded the spin-off company Sanejament Intel·ligent S.L. (SISLtech, 2003-2017), which received the Energy Excellence Award 2013, and the Bioenergy Silver Award 2012. He is a pioneer member of Catalan Association of Artificial Intelligence (ACIA) and in 1994-1998 was member of its board of directors. He is a Fellow of the International Environmental Modelling and Software Society (iEMSs) since 2005. He co-organized the first Environment and AI Workshop in Europe: Binding Environmental Sciences and Artificial Intelligence (BESAI 98) at ECAI conference in 1998, and mentioned for that as contributor to the “Timeline of Artificial Intelligence” in Wikipedia. He is member of Spanish Association for Artificial Intelligence (AEPIA) and a pioneer member of iEMSs and a board member of iEMSs, too. He is also a pioneer member of the MIDAS (Spanish Network on Data Mining and Learning) and ĮTICA (Spanish network on Advance and Transference of Applied Computational Intelligence), and he was the main coordinator of the ĮTICA network. His main research topics are Intelligent Decision Support Systems, Case-Based Reasoning, Machine Learning, Data Science, Recommender Systems, Knowledge Engineering, Integrated AI architectures, and AI applied to Environmental, Industrial and Health systems. He is author of 220 peer-reviewed publications, including 6 other books.

From the Back Cover

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 usingmodel-driven methods and for aiding the development of Intelligent Decision Support Systems

Edition details

• Publisher: Springer
• Publication date: 2022
• ISBN 10: 3030877892
• ISBN 13: 9783030877897
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 836