title: Diagnostic expert system using non-monotonic reasoning
abstract: The objective of this work is to develop an expert system for cucumber disorder diagnosis using non-monotonic reasoning to handle the situation when the system cannot reach a conclusion. One reason for this situation is when the information is incomplete. Another reason is when the domain knowledge itself is incomplete. Another reason is when the information is inconsistent. This method maintains the truth of the system in case of changing a piece of information. The proposed method uses two types of non-monotonic reasoning namely: default reasoning and reasoning in the presence of inconsistent information to achieve its goal
keyphrases: diagnostic expert system cucumber disorder diagnosis default reasoning inconsistent information nonmonotonic reasoning incomplete information truth maintenance agriculture