AIJul 11, 2012

Compact Value-Function Representations for Qualitative Preferences

arXiv:1207.4126v131 citations
Originality Incremental advance
AI Analysis

This work addresses the problem of efficient preference modeling for users in database systems, but it appears incremental as it builds on existing factored representation models.

The paper tackles the challenge of preference elicitation for selecting desirable items from a database by developing strong representation theorems for factored value functions and a methodology for optimal item selection, though no concrete numbers are provided.

We consider the challenge of preference elicitation in systems that help users discover the most desirable item(s) within a given database. Past work on preference elicitation focused on structured models that provide a factored representation of users' preferences. Such models require less information to construct and support efficient reasoning algorithms. This paper makes two substantial contributions to this area: (1) Strong representation theorems for factored value functions. (2) A methodology that utilizes our representation results to address the problem of optimal item selection.

Foundations

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