State space search nogood learning: Online refinement of critical-path dead-end detectors in planning-Reference-Cited by-同舟云学术

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State space search nogood learning: Online refinement of critical-path dead-end detectors in planning

Published:2017-04 Issue: Volume:245 Page:1-37
ISSN:0004-3702
Container-title:Artificial Intelligence
language:en
Short-container-title:Artificial Intelligence

Author:

Steinmetz Marcel,Hoffmann Jörg

Funder

German Research Foundation

DFG

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference94 articles.

1. Enhancement schemes for constraint processing: backjumping, learning, and cutset decomposition;Dechter;Artif. Intell.,1990

2. Hybrid algorithms for the constraint satisfaction problem;Prosser;Comput. Intell.,1993

3. GRASP: a search algorithm for propositional satisfiability;Marques-Silva;IEEE Trans. Comput.,1999

4. Chaff: engineering an efficient SAT solver;Moskewicz,2001

5. Backjump-based backtracking for constraint satisfaction problems;Dechter;Artif. Intell.,2002

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unavoidable deadends in deterministic partially observable contingent planning;Autonomous Agents and Multi-Agent Systems;2022-10-29

2. Search and Compare Drives Satisfaction;International Journal of Customer Relationship Marketing and Management;2022-01

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