Abstract
The system LEFT is presented that learns most specific generalizations (MSGs) from structural descriptions. The new inductive multi-staged generalization algorithm is based on several new or enhanced concepts that improve the quality of generalization and make it applicable to real-world problems: LEFT evaluates the quality of each generated MSG using weighted predicates. The algorithm distinguishes between important and less-important predicates. Built-in predicates are used to improve the resulting hypothesis. The system has been applied successfully to chip-floorplanning — a subtask of VLSI-design.
There are multiple different ways to assign the objects of one example consistently to the objects of another one. Each of these combinations of object bindings can lead to a different MSG. For two examples with n objects there can be up to n! different combinations.
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© 1993 Springer-Verlag Berlin Heidelberg
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Herrmann, J., Beckmann, R. (1993). A heuristic inductive generalization method and its application to VLSI-design. In: Jürgen Ohlbach, H. (eds) GWAI-92: Advances in Artificial Intelligence. Lecture Notes in Computer Science, vol 671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0019003
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DOI: https://doi.org/10.1007/BFb0019003
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