Expected Utility Based Decision Making under Z -Information and Its Application

Abstract

Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 34 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.