资源论文Computing Minimum-Cardinality Diagnoses by Model Relaxation Sajjad Siddiqi

Computing Minimum-Cardinality Diagnoses by Model Relaxation Sajjad Siddiqi

2019-11-12 | |  62 |   41 |   0
Abstract self-contained sub-systems called cones as single components. We then use a novel branchand-bound search algorithm and compute the abstract minimum-cardinality diagnoses of the system, which are later re?ned hierarchically, in a careful manner, to get all minimum-cardinality diagnoses of the system. Experiments on ISCAS-85 benchmark circuits show that the new approach is faster than the previous state-of-the-art hierarchical approach, and scales to all circuits in the suite for the ?rst time.

上一篇:Description Logics and Fuzzy Probability Lutz Schro?der Dirk Pattinson

下一篇:Consequence-Based Reasoning beyond Horn Ontologies ? František Simanc?ík and Yevgeny Kazakov and Ian Horrocks

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...