Probabilistic Conditional Preference Networks
In order to represent the preferences of a group of individuals, we introduce Probabilistic CP-nets (PCP-nets). PCP-nets provide a compact language for representing probability distributions over preference orderings. We argue that they are useful for aggregating preferences or modelling noisy preferences. Then we give efficient algorithms for the main reasoning problems, namely for computing the probability that a given outcome is preferred to another one, and the probability that a given outcome is optimal. As a by-product, we obtain an unexpected linear-time algorithm for checking dominance in a standard, tree-structured CP-net.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Active Preference Inference using Language Models and Probabilistic Reasoning
Actively inferring user preferences, for example by asking good questions, is important for any human-facing decision-making system. Active inference allows such systems to adapt and personalize themselves to nuanced ind…
Decision MakingA conditional, a fuzzy and a probabilistic interpretation of self-organising maps
In this paper we establish a link between fuzzy and preferential semantics for description logics and Self-Organising Maps, which have been proposed as possible candidates to explain the psychological mechanisms underlyi…
Multi-Objective Exploration and Preference Optimization via Mutual Information
Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicting preference dimensions. Current methods achieve this trade-off by …
Logical Conditional Preference Theories
CP-nets represent the dominant existing framework for expressing qualitative conditional preferences between alternatives, and are used in a variety of areas including constraint solving. Over the last fifteen years, a s…
Introducing Super Pseudo Panels: Application to Transport Preference Dynamics
We propose a new approach for constructing synthetic pseudo-panel data from cross-sectional data. The pseudo panel and the preferences it intends to describe is constructed at the individual level and is not affected by …