Comparing AI Search Algorithms and Their Efficiency When Applied to Path Finding Problems
Item
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Title
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Comparing AI Search Algorithms and Their Efficiency When Applied to Path Finding Problems
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Identifier
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d_2009_2013:c7be2722f671:11576
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identifier
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12122
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Creator
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Kose, Erdal,
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Contributor
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Danny Kopec
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Date
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2012
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Language
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English
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Publisher
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City University of New York.
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Subject
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Computer science | Artificial intelligence
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Abstract
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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.
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Type
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dissertation
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Source
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2009_2013.csv
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degree
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Ph.D.
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Program
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Computer Science
