Conditional Preference Networks with User's Genuine Decisions. (29th July 2020)

• Record Type: Journal Article
• Authors: Ahmed, Sultan; Mouhoub, Malek
• Is Part Of: Computational intelligence. Volume 36:Number 3(2020)
• Page Start: 1414
• Page End: 1442
• Publication Date: 2020-07-29
• Subjects: backtrack search -- CP‐net -- Pareto optimality -- preferences; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12386
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: User's choices involve habitual behavior and genuine decision. Habitual behavior is often expressed using preferences. In a multiattribute case, the Conditional Preference Network (CP‐net) is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. Indeed, the CP‐net induces a strict partial order over the outcomes. By contrast, we argue that genuine decisions are environmentally influenced and introduce the notion of "comfort" to represent this type of choices. In this article, we propose an extension of the CP‐net model that we call the CP‐net with Comfort (CPC‐net) to represent a user's comfort with preferences. Given that preference and comfort might be two conflicting objectives, we define the Pareto optimality of outcomes when achieving outcome optimization with respect to a given CPC‐net. Then, we propose a backtrack search algorithm to find the Pareto optimal outcomes. On the other hand, two outcomes can stand in one of six possible relations with respect to a CPC‐net. The exact relation can be obtained by performing dominance testing in the corresponding CP‐net and comparing the numeric comforts.