Abstract
This paper develops algorithms for dynamically consistent updating of ambiguous beliefs in the maxmin expected utility model of decision making under ambiguity. Dynamic consistency is the requirement that ex-ante contingent choices are respected by updated preferences. Such updating, in this context, implies dependence on the feasible set of payoff vectors available in the problem and/or on an ex-ante optimal act for the problem. Despite this complication, the algorithms are formulated concisely and are easy to implement, thus making dynamically consistent updating operational in the presence of ambiguity.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1198-1214 |
| Number of pages | 17 |
| Journal | International Journal of Approximate Reasoning |
| Volume | 52 |
| Issue number | 8 |
| DOIs | |
| State | Published - Nov 2011 |
Funding
We thank Yigal Gerchak, Tal Raviv, two anonymous referees, the area editor and Thierry Denoeux, the Editor-in-Chief, for helpful discussions and comments. This research was partially supported by Grant No. 2006264 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Israel. All responsibility for the contents of the paper lies solely with the authors.
Keywords
- Ambiguity
- Risk analysis
- Uncertainty modeling
- Updating beliefs
- Utility theory
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics