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2010 Volume 25
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RESEARCH ARTICLE   Open Access    

Generation of macro-operators via investigation of action dependencies in plans

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  • Corresponding author: Lukáš Chrpa

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RESEARCH ARTICLE   Open Access    

Generation of macro-operators via investigation of action dependencies in plans

  • Corresponding author: Lukáš Chrpa
The Knowledge Engineering Review  25 Article number: 10.1017/S0269888910000159  (2010)  |  Cite this article

Abstract: Abstract: There are many approaches for solving planning problems. Many of these approaches are based on ‘brute force’ search methods and they usually do not care about structures of plans previously computed in particular planning domains. By analyzing these structures, we can obtain useful knowledge that can help us find solutions to more complex planning problems. The method described in this paper is designed for gathering macro-operators by analyzing training plans. This sort of analysis is based on the investigation of action dependencies in training plans. Knowledge gained by our method can be passed directly to planning algorithms to improve their efficiency.

    • The research is supported by the Czech Science Foundation under contract nos 201/08/0509 and 201/05/H014.

    • The results of LPG are only briefly reported.

    • Available on IPC4 website.

    • Can be obtained on http://ipc.icaps-conference.org

    • Performed on XEON 2.4GHz, 1GB RAM, Ubuntu Linux.

    • Performed on Core2Duo 2.66GHz, 4GB RAM, Win XP SP2.

    • A ratio of the length of the plans in the original domains and the length of the plans in the updated domains—macro-actions are unfolded into primitive actions.

    • Copyright © Cambridge University Press 20102010Cambridge University Press
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    Lukáš Chrpa. 2010. Generation of macro-operators via investigation of action dependencies in plans. The Knowledge Engineering Review. 25: doi: 10.1017/S0269888910000159
    Lukáš Chrpa. 2010. Generation of macro-operators via investigation of action dependencies in plans. The Knowledge Engineering Review. 25: doi: 10.1017/S0269888910000159
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