Home | Publications | CS Home

Publications Related to: Speedup Learning

By Shaul Markovitch

  1. Carmel Domshlak, Erez Karpas and Shaul Markovitch. Online Speedup Learning for Optimal Planning. Journal of Artificial Intelligence Research, 44:709-755 2012.[abstract][pdf]
  2. Carmel Domshlak, Erez Karpas and Shaul Markovitch. To Max or Not to Max: Online Learning for Speeding Up Optimal Planning. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 1071-1076 Atlanta, Georgia, 2010.[abstract][pdf]
  3. Carmel Domshlak, Erez Karpas and Shaul Markovitch. Learning to Combine Admissible Heuristics Under Bounded Time. In Proceedings of the ICAPS 2009 Workshop on Planning and Learning, Thessaloniki, Greece, 2009.[abstract][pdf]
  4. Dmitry Davidov and Shaul Markovitch. Multiple-goal Heuristic Search. Journal of Artificial Intelligence Research, 26:417-451 2006.[abstract][pdf]
  5. Shaul Markovitch and Asaf Shatil. Speedup Learning for Repair-based Search by Identifying Redundant Steps. Journal of Machine Learning Research, 4:649-682 2003.[abstract][pdf]
  6. Orna Grumberg, Shlomi Livne and Shaul Markovitch. Learning to Order {BDD} Variables in Verification. Journal of Artificial Intelligence Research, 18:83-116 2003.[abstract][pdf]
  7. Dmitry Davidov and Shaul Markovitch. Multiple-goal Search Algorithms and their Application to Web Crawling. In Proceedings of the Eighteenth National Conference on Artificial Intelligence, 713-718 Edmonton, Alberta, Canada, 2002.[abstract][pdf]
  8. Shaul Markovitch. Applications of Macro Learning to Path Planning. Technical report CIS9907, Technion, 1999.[abstract][pdf]
  9. Oleg Ledeniov and Shaul Markovitch. The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference. Journal of Artificial Intelligence Research, 9:37-97 1998.[abstract][pdf]
  10. Lev Finkelstein and Shaul Markovitch. A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. Journal of Artificial Intelligence Research, 8:223-263 1998.[abstract][pdf]
  11. Oleg Ledeniov and Shaul Markovitch. Learning Investment Functions for Controlling the Utility of Control Knowledge. In Proceedings of the Fifteenth National Conference on Artificial Intelligence, 463-468 Madison, Wisconsin, 1998.[abstract][pdf]
  12. Oleg Ledeniov and Shaul Markovitch. Controlled Utilization of Control Knowledge for Speeding up Logic Inference. Technical Report CIS9812, Technion, 1998.[abstract][pdf]
  13. Uri Keidar, Shaul Markovitch and Erez Webman. Utilization Filtering of Macros Based on Goal Similarity. Technical Report CIS9608, Technion, 1996.[abstract][pdf]
  14. Shaul Markovitch and Paul Scott. Information Filtering: Selection Mechanisms in Learning Systems. Machine Learning, 10:113-151 1993.[abstract][pdf]
  15. Shaul Markovitch and Paul Scott. Utilization Filtering: a Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge. In Proceedings of The Eleventh International Joint Conference for Artificial Intelligence, 738-743 Detroit, Michigan, 1989.[abstract][pdf]
  16. Shaul Markovitch and Paul Scott. Automatic Ordering of Subgoals --- A Machine Learning Approach. In Proceedings of the North American Conference on Logic Programming, 224-242 Cleveland, Ohio, USA, 1989.[abstract][pdf]