Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development
IEEE Transactions on Software Engineering - Special issue on artificial intelligence and software engineering
CommonKADS: A Comprehensive Methodology for KBS Development
IEEE Expert: Intelligent Systems and Their Applications
The unified problem-solving method development language UPML
Knowledge and Information Systems
Knowledge coding methods for rule-based expert systems
WSEAS Transactions on Information Science and Applications
Monitoring distributed parameter systems based on expert systems and sensor networks
NNECFSIC'12 Proceedings of the 12th WSEAS international conference on Neural networks, fuzzy systems, evolutionary computing & automation
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Humans seem to have a natural instinct for wanting to understand and make sense of their environment and things in it. In expert systems (ES), explanation can be used to clarify the reasoning process to users such that they can gain a better understanding of how the system functions. With the help of good explanation facilities, a user can know why an ES is asking a particular question, how the expert system will act if given a certain input, and how the ES reaches a particular conclusion. This is especially important when an ES application is used as a high level advisor to professionals who must retain responsibility for the decisions which are made. However, most ES explanation components require acquiring additional knowledge for explanation, thus increasing the effort of implementing an ES with explanation capabilities. The primary goal of this work is to present a methodology for automatically generating explanations during and at the end of the reasoning process. The developed explanation components can deal with different knowledge representation schemes that are used by problem solving methods namely, the "generate and confirm hypotheses" that is based on the CommonKADS methodology[1], and the routine design generic task[2]. As a proof of concept the explanation components were developed and integrated into the agricultural expert system generic tool (AESGT)[3]. The developed explanation components can be easily reused with expert systems developed by the tool to automatically generate explanation for the reasoning process.