Transaction-Based Knowledge Acquisition: Complex Modications Made Easier

Our goal is to build knowledge acquisition tools that support users in making a broad range of changes to a knowledge base, including both factual and problem-solving knowledge. These changes may require several individual modi cations to various parts of the knowledge base, that need to be carefully coordinated to prevent users from introducing errors in the knowledge base. Thus, it becomes essential that our KA tools understand the consequences of each kind of change that the user may initiate, detect any harmful side-e ects that can be introduced in the system, and guide the user in resolving them. To address this issue, we have developed a transaction-based approach to knowledge acquisition that can support users in making complex modi cations to a knowledge base. A transaction is a sequence of changes that together modify some aspect of the behavior of a knowledge-based system, and that when only partially carried out may leave the knowledge base in an undesirable state. If a user executes a transaction partially, the knowledge acquisition tool must provide guidance to nish it and support the user in achieving the desired modi cation. This paper also describes our work in extending EXPECT's knowledge acquisition tool to support transaction-based mechanisms. EXPECT tracks the possible problems that arise as a consequence of each individual change to the knowledge base, keeps information about the context of each change, and uses this context to resolve the problems detected and to request the user's intervention if additional information is needed.