Reasons and Means to Model Preferences as Incomplete
arXiv:1801.01657v11 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental review paper that synthesizes existing literature on preference modeling for AI and human decision-making.
The paper reviews reasons for modeling preferences as incomplete rather than complete transitive binary relations, and surveys techniques for constructing such models.
Literature involving preferences of artificial agents or human beings often assume their preferences can be represented using a complete transitive binary relation. Much has been written however on different models of preferences. We review some of the reasons that have been put forward to justify more complex modeling, and review some of the techniques that have been proposed to obtain models of such preferences.