ABSTRACT
Temporal reasoning and reasoning under uncertainty are two important issues in artificial intelligence and expert/knowledge-based systems. The question is raised of how to represent uncertain times and model temporal relationships among them. This in turn gives rise to the issue of how binary relations over a domain can be handled when uncertainty in the domain is modelled according to some relevant theory, such as probability theory or evidential theory. Although there has been work to tackle this information handling problem in some specific cases, no explicit general work exists. This paper identifies a general framework with which the problem can be tackled. A series of algorithms in the setting of evidential theory are presented and some related specific work is analysed accordingly.
