Agent oriented fault detection, isolation and recovery and aspect-oriented plug-and-play tracking mechanism

Fault detection, isolation, and recovery are some of the most critical activities in which astronauts and flight controllers participate. Recent systems to perform the FDIR activity lack portability and extensibility, and do not provide any explanation of the system's activity. In this research, we explore the use of an agent-oriented paradigm and Java technology for better performance of FDIR activity. Also, we have explored the use of explanation in agent-oriented systems, and designed a system-activity tracking mecha-nism that helps the user to understand the agents' behavior. We have explored different ways to generalize this mechanism for arbitrary agent systems to use. Furthermore, we studied mechanisms to automatically add the tracking mechanism to an existing agent system. By using AspectJ, an aspect-oriented tool, a plug-and-playable tracking system has been built that can add the capability to track the activity of the system to any JACK agent system easily. Our experience can help further research on using aspect-oriented tools with agent-oriented paradigms together to obtain better performance

Presenting Significant Information in Expert System Explanation

. This paper presents a method for eliminating insigni#cant portions of an explanation of a conclusion # those portions that include terminology and inferences that the user does not have the expertise to understand# and those portions that add little to the user#s belief in the conclusion. The method exploits a user model to select for presentation only those portions of an expert system#s reasoning that add signi## cantly to the user#s belief that the conclusion is the right one. Examples demonstrate how the method generates concise explanations with only signi#cant information# and how it tailors the explanation to the user. 1 Satis#cing Explanations Today#s knowledge#based systems can use quite complex chains of reasoning to produce conclusions# and producing good machine#generated explanations for those conclusions can be di#cult. Some explanations will involve complex do# main concepts and detailed reasoning steps that the user has no hope of under# standing. These kind..