The need for an automatic inference process able to deal with information coming from unreliable sources is becoming a relevant issue both on corporate networks and on the open Web...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
The need to merge multiple sources of uncertain information is an important issue in many application areas, especially when there is potential for contradictions between sources. ...
Semi-structured information in XML can be merged in a logic-based framework [Hun02, Hun02b]. This framework has been extended to deal with uncertainty, in the form of probability ...
This paper discusses the problem of efficient propagation of uncertain information in dynamic environments and critical situations. When a number of (distributed) agents have only ...
Uncertain information is commonplace in real-world data management scenarios. The ability to represent large sets of possible instances (worlds) while supporting efficient storage ...
In possibility theory, the degree of inconsistency is commonly used to measure the level of conflict in information from multiple sources after merging, especially conjunctive merg...
Abstract. We present a novel approach to representing uncertain information in ontologies based on design patterns. We provide a brief description of our approach, present its use ...
Abstract. The two puzzles are the Lottery Paradox and the Amalgamation Paradox, which both point out difficulties for aggregating uncertain information. A generalization of the lot...
— We propose a robot path planning method based on particle swarm optimization in an uncertain environment. We consider the case that a robot’s cognition to its environment is ...