LEFT—A SYSTEM THAT LEARNS RULES ABOUT VLSI DESIGN FROM STRUCTURAL DESCRIPTIONS
作者:
JÜRGEN HERRMANN,
RENATE BECKMANN,
期刊:
Applied Artificial Intelligence
(Taylor Available online 1994)
卷期:
Volume 8,
issue 1
页码: 85-108
ISSN:0883-9514
年代: 1994
DOI:10.1080/08839519408945433
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
The system presented, LEFT, learns most specific generalizations (MSGs)from structural descriptions. The new inductive multistaged generalization algorithm is based on several new or enhanced ideas that improve the quality of generalization using weighted predicates and make it applicable to real world problems. The algorithm distinguishes between important and less important predicates. Built-in predicates are used to select alternative MSGs and improve the resulting hypothesis. The system has been applied successfully to chip-floorplanning, a subtask of VLSI design. It acquires rules describing single floorplanning steps.
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