Approximate reasoning for contextual databases

Contextual reasoning has been proposed as a tool for solving the problem of generality in AI and for effectively handling huge knowledge bases, while approximate reasoning has been developed to overcome the computational barrier of classical deduction. This paper combines these approaches to provide an intuitive representation of knowledge and an effective deduction. Its semantics and a tableau calculus are presented. The key computational features are discussed.