47 citations · 109 across the 6 of their papers we have counts for
5 papers · 1 filter
Theoretical Foundations for Abstraction-Based Probabilistic Planning
Vu A. Ha, Peter Haddawy
Modeling worlds and actions under uncertainty is one of the central problems in the framework of decision-theoretic planning. The representation must be general enough to capture r…
Problem-Focused Incremental Elicitation of Multi-Attribute Utility Models
Vu A. Ha, Peter Haddawy
Decision theory has become widely accepted in the AI community as a useful framework for planning and decision making. Applying the framework typically requires elicitation of some…
Towards Case-Based Preference Elicitation: Similarity Measures on Preference Structures
Vu A. Ha, Peter Haddawy
While decision theory provides an appealing normative framework for representing rich preference structures, eliciting utility or value functions typically incurs a large cost. For…
A Hybrid Approach to Reasoning with Partially Elicited Preference Models
Vu A. Ha, Peter Haddawy
Classical Decision Theory provides a normative framework for representing and reasoning about complex preferences. Straightforward application of this theory to automate decision m…
Similarity Measures on Preference Structures, Part II: Utility Functions
Vu A. Ha, Peter Haddawy, John Miyamoto
In previous work cite{Ha98:Towards} we presented a case-based approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity bet…