2013/03/20 by Enrique H. Ruspini, Ruspini, Enrique H.
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #cs.AI
paper · pdf · doi:10.48550/arxiv.1303.5744
Appears in Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence (UAI1991)
arxiv created 2013/03/20 · openalex publication_date 2013/03/20 · arxiv updated 2013/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper introduces conceptual relations that synthesize utilitarian and logical concepts, extending the logics of preference of Rescher. We define first, in the context of a possible worlds model, constraint-dependent measures that quantify the relative quality of alternative solutions of reasoning problems or the relative desirability of various policies in control, decision, and planning problems. We show that these measures may be interpreted as truth values in a multi valued logic and propose mechanisms for the representation of complex constraints as combinations of simpler restrictions. These extended logical operations permit also the combination and aggregation of goal-specific quality measures into global measures of utility. We identify also relations that represent differential preferences between alternative solutions and relate them to the previously defined desirability measures. Extending conventional modal logic formulations, we introduce structures for the representation of ignorance about the utility of alternative solutions. Finally, we examine relations between these concepts and similarity based semantic models of fuzzy logic.