Decision Theory With Imperfect Information

Every day decision making in complex human-centric systems are characterized by imperfect decision-relevant information. The principal problems with the existing decision theories are that they do not have capability to deal with situations in which probabilities and events are imprecise. In this book, we describe a new theory of decision making with imperfect information. The aim is to shift the foundation of decision analysis and economic behavior from the realm bivalent logic to the realm fuzzy logic and Z-restriction, from external modeling of behavioral decisions to the framework of combined states.

This book will be helpful for professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.
Contents: Theories of Decision Making under UncertaintyFuzzy Logic and Approximate ReasoningPreferences FrameworkImperfect Decision-Relevant InformationUncertainty Measures in Decision MakingFuzzy Logic-Based Decision Theory with Imperfect InformationHierarchical Models for Decision Making with Imperfect InformationDecision Making Model without UtilityBehavioral Decision Making with Combined States under Imperfect InformationDecision Making under Unprecisiated Imperfect InformationThe General Theory of DecisionsSimulations and Applications
Readership: Professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.