Automatic Knowledge Acquisition for Object-Oriented Expert Systems
This work addresses knowledge acquisition for expert systems, but it appears incremental as it builds on existing object-oriented models with a focus on similarity-based induction.
The paper tackles the problem of knowledge acquisition for object-oriented expert systems by proposing original algorithms that handle total and partial structural similitude of objects, enabling reasoning modes like induction, deduction, and simulation.
We describe an Object Oriented Model for building Expert Systems. This model and the detection of similarities allow to implement reasoning modes as induction, deduction and simulation. We specially focus on similarity and its use in induction. We propose original algorithms which deal with total and partial structural similitude of objects to facilitate knowledge acquisition.