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Sub Goal Oriented A* Search

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Artificial Intelligence and Mobile Services – AIMS 2018 (AIMS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10970))

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Abstract

Search is a well-studied paradigm of Artificial Intelligence (AI). The complexity of various search algorithms is measured in terms of space, and time to solve a problem. Blind search methods use too much space or too much time to solve a problem. Informed search algorithms such as Best First Search, A* overcomes these handicaps of blind search techniques by employing heuristics, but for hard problems heuristic search algorithms are also facing time and space problem. In the following study we present a new informed sub-goal oriented form of A* search algorithm. We call it “Sub-Goal Oriented A* Search (SGOA*)”, it uses less space and time to solve certain search problems which have well-known sub-goals. If we employ an admissible heuristic, then SGOA* is optimal. The algorithm has been applied to a group of fifteen puzzles.

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Author information

Authors and Affiliations

  1. Department of Engineering and Computer Science, Fairleigh Dickinson University, Teaneck Campus, 1000 River Road, Teaneck, NJ, 07666, USA

    Erdal Kose

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  1. Erdal Kose
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Correspondence to Erdal Kose .

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Editors and Affiliations

  1. University of Stuttgart, Stuttgart, Germany

    Marco Aiello

  2. Tsinghua University, Beijing, China

    Yujiu Yang

  3. Peking University, Beijing, China

    Yuexian Zou

  4. Kingdee International Software Group Co., Ltd., Shenzhen, China

    Liang-Jie Zhang

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Kose, E. (2018). Sub Goal Oriented A* Search. In: Aiello, M., Yang, Y., Zou, Y., Zhang, LJ. (eds) Artificial Intelligence and Mobile Services – AIMS 2018. AIMS 2018. Lecture Notes in Computer Science(), vol 10970. Springer, Cham. https://doi.org/10.1007/978-3-319-94361-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-94361-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94360-2

  • Online ISBN: 978-3-319-94361-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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