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.

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

Table of Contents

Chapter 1. Theories of Decision Making under Uncertainty
Chapter 2. Fuzzy Logic and Approximate Reasoning
Chapter 3. Preferences Framework
Chapter 4. Imperfect Decision-Relevant Information
Chapter 5. Uncertainty Measures in Decision Making
Chapter 6. Fuzzy Logic-Based Decision Theory with Imperfect Information
Chapter 7. Hierarchical Models for Decision Making with Imperfect Information
Chapter 8. Decision Making Model without Utility
Chapter 9. Behavioral Decision Making with Combined States under Imperfect Information
Chapter 10. Decision Making under Unprecisiated Imperfect Information
Chapter 11. The General Theory of Decisions
Chapter 12. Simulations and Applications