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MEvo: a framework for effective macro sets evolution

  • Published:2019-09-30 Issue:4 Volume:32 Page:685-703
  • ISSN:0952-813X
  • Container-title:Journal of Experimental & Theoretical Artificial Intelligence
  • language:en
  • Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Vallati Mauro1,Chrpa Lukáš23,Serina Ivan4

Affiliation:

1. Department of Informatics, University of Huddersfield, Huddersfield, UK

2. Department of Computer Science, Czech Technical University in Prague, Prague, Prague Czech Republic

3. Department of Theoretical Computer Science and Mathematical Logic, Charles University in Prague, Prague, Prague Czech Republic

4. Dipartimento d’Ingegneria dell’Informazione, Universitá degli Studi di Brescia, Brescia, Italy

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Cited by 3 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. Reformulation techniques for automated planning: a systematic review;The Knowledge Engineering Review;2023

2. Improving Domain-Independent Heuristic State-Space Planning via plan cost predictions;Journal of Experimental & Theoretical Artificial Intelligence;2021-10-31

3. Configurable Heuristic Adaptation for Improving Best First Search in AI Planning;2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI);2020-11
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