Goal-directed Software Assistant for a Planning Advisory System
نویسنده
چکیده
In this paper, I present an assistant program for a scientific plan advisory system that can help amateur users identify problems in unexpected situations and find related instructions for resolving them. This assistant program uses commonsense reasoning to map the users’ problem descriptions into related concepts used by the advisory system, and to generate explanations for the possible causes of failure and instructions on recovery procedures using the system. The commonsense reasoning layer resolves the mismatch between the users’ knowledge and the advisory system’s model, and therefore enables the user to easily communicate to the system’s high functionality interface.
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