CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

By Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole. Journal of Artificial Intelligence Research, 2011

953 citations recorded by the source corpus.

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitative way. In this paper, we propose a qualitative graphical representation of preferences that reflects conditional dependence and independence of preference statements under a ceteris paribus (all else being equal) interpretation. Such a representation is often compact and arguably quite natural in many circumstances. We provide a formal semantics for this model, and describe how the structure of the network can be exploited in several inference tasks, such as determining whether one outcome dominates (is preferred to) another, ordering a set outcomes according to the preference relation, and constructing the best outcome subject to available evidence.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/349d84b45973c5b5fdaf5b0b567bb128a0e131cc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Johannes Fürnkranz
2. Stefano V. Albrecht
3. Eyke Hüllermeier
4. Weiwei Cheng
5. Peter Stone
6. Julian A. Padget
7. Ronald E. Parr
8. Yann Chevaleyre

In Computer Networks and Communications

1. Peter Stone
2. Ronald E. Parr
3. Eyke Hüllermeier
4. Yann Chevaleyre
5. Johannes Fürnkranz
6. Stefano V. Albrecht

In Signal Processing

1. Eyke Hüllermeier
2. Johannes Fürnkranz
3. Weiwei Cheng
4. Peter Stone
5. Stefano V. Albrecht
6. Min-Ling Zhang
7. Mohammad S. Sorower
8. Qiang Ji

Citations in the corpus

• Label ranking by learning pairwise preferences (2008, background): “Finally, every preference statement in the well-known CP-nets approach [8], a qualitative graphical representation that reflects conditional dependence and independence of preferences under a ceteris paribus interpretation, formally corresponds to a label ranking.”
• The role of fuzzy sets in decision sciences: Old techniques and new directions (2011, neutral): “The worst case is when max(0, 0, . . . , 0, λi) > max(λi−1, . . . , λi−1).”
• DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks (2009, methodology): “CP-nets and related formalisms [Boutilier et al. , 2004; Brafman et al. , 2006; Wilson, 2004a] allow only very restricted forms of comparative preference statements.”
• Autonomous agents modelling other agents: A comprehensive survey and open problems (2017, background): “Cadilhac et al. (2013) use conditional preference (CP) networks (Boutilier et al., 2004) to model the preferences of players based on their negotiation dialogues.”
• Issues in Multiagent Resource Allocation (2006, background): “For instance, TCP-nets [12] are CP-nets with a dominance relation between variables.”