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Comparing AI Search Algorithms and Their Efficiency When Applied to Path Finding Problems.

机译:当应用于路径查找问题时,比较AI搜索算法及其效率。

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摘要

Various Artificial Intelligence (AI) search algorithms have been investigated and classified as unidirectional or bidirectional. We start our discussion by presenting certain unidirectional and bidirectional search algorithms (BDS). We continued our study by presenting contributions to the field of search algorithms in AI. The focus of this research is the study of the bidirectional search and certain classes of AI problems and some new approaches to the domain of AI search algorithms have been explored. The second contribution of this research is to compare problem representations and to exploit built-in features of diverse programming paradigms. The programing paradigms have been classified by the problem domains which they might be more suitable for. This has been justified by the fact that the evaluation of search algorithms is a well-studied area of Artificial Intelligence (AI). However evaluation of the performance of programming paradigms when applied to search algorithms has not been studied well. We conclude our discussion with experimental results and more detailed information about our implementations.
机译:已经研究了各种人工智能(AI)搜索算法,并将其分类为单向或双向。我们通过介绍某些单向和双向搜索算法(BDS)开始讨论。通过介绍对AI搜索算法领域的贡献,我们继续了我们的研究。这项研究的重点是双向搜索和某些类型的AI问题的研究,并且探索了一些新的方法来搜索AI搜索算法。这项研究的第二个贡献是比较问题表示形式并利用各种编程范例的内置功能。编程范式已按可能更适合的问题域进行了分类。事实证明,搜索算法的评估是人工智能(AI)领域中经过深入研究的事实。但是,当将编程范例应用于搜索算法时,其性能评估尚未得到很好的研究。我们以实验结果和有关实现的更详细信息来结束讨论。

著录项

  • 作者

    Kose, Erdal.;

  • 作者单位

    City University of New York.;

  • 授予单位 City University of New York.;
  • 学科 Artificial Intelligence.;Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 205 p.
  • 总页数 205
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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