Abstract. In this paper we consider a logic programming framework for reasoning about imprecise probabilities. In particular, we propose a new semantics, for the Probabilistic Logi...
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
The relational algebra and calculus do not take the semantics of terms into account when answering queries. As a consequence, not all tuples that should be returned in response to ...
Octavian Udrea, Yu Deng, Edward Hung, V. S. Subrah...
We introduce a general framework for reasoning with prioritized propositional data by aggregation of distance functions. Our formalism is based on a possible world semantics, wher...
Abstract. This paper describes a system called SELP for studying strong equivalence in answer set logic programming. The basic function of the system is to check if two given groun...