Aggregating Imprecise Probabilistic Knowledge
نویسندگان
چکیده
The problem of aggregating two or more sources of information containing knowledge about a same domain is considered. We propose an aggregation rule for the case where the available information is modeled by coherent lower previsions, corresponding to convex sets of probability mass functions. The consistency between aggregated beliefs and sources of information is discussed. A closed formula, which specializes our rule to a particular class of models, is also derived. Finally, an alternative explanation of Zadeh’s paradox is provided.
منابع مشابه
Reasoning with imprecise probabilistic knowledge on enzymes for rapid screening of potential substrates or inhibitor structures
In many applications, there is a need to model and reason with imprecise probabilistic knowledge. In this paper, we discuss how to model imprecise probabilistic knowledge obtained from experiments in biological sciences on enzymes for rapid screening of potential substrate or inhibitor structures. Each imprecise probabilistic knowledge base is modelled as a probabilistic logic program (PLP). To...
متن کاملRevising Imprecise Probabilistic Beliefs in the Framework of Probabilistic Logic Programming
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base which contains a set of conditional events with probability intervals. In this paper, we investigate the issue of revising such a PLP in light of receiving new information. We propose postulates for revising PLPs when a n...
متن کاملProbabilistic Satisfiability with Imprecise Probabilities
Treatment of imprecise probabilities within the probabilistic satis®ability approach to uncertainty in knowledge-based systems is surveyed and discussed. Both probability intervals and qualitative probabilities are considered. Analytical and numerical methods to test coherence and bound the probability of a conclusion are reviewed. They use polyhedral combinatorics and advanced methods of linea...
متن کاملA Syntax-based Framework for Merging Imprecise Probabilistic Logic Programs
In this paper, we address the problem of merging multiple imprecise probabilistic beliefs represented as Probabilistic Logic Programs (PLPs) obtained from multiple sources. Beliefs in each PLP are modeled as conditional events attached with probability bounds. The major task of syntax-based merging is to obtain the most rational probability bound for each conditional event from the original PLP...
متن کاملA ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge
Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009