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 Uncertainty
• Fuzzy Logic and Approximate Reasoning
• Preferences Framework
• Imperfect Decision-Relevant Information
• Uncertainty Measures in Decision Making
• Fuzzy Logic-Based Decision Theory with Imperfect Information
• Hierarchical Models for Decision Making with Imperfect Information
• Decision Making Model without Utility
• Behavioral Decision Making with Combined States under Imperfect Information
• Decision Making under Unprecisiated Imperfect Information
• The General Theory of Decisions
• Simulations and Applications

Readership: Professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.