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In Artificial Intelligence knowledge representation is a combination of data structures and interpretive procedures that leads to knowledgeable behavior. It is required to investigate such knowledge representation technique in which knowledge can be easily represented in computer. This book compares various knowledge representation techniques and proves that predicate logic is more efficient and accurate knowledge representation scheme. The algorithm presented in this book splits the English text into phrases/constituents and then represents these in predicate logic. Another algorithm splits the Urdu text into phrases/constituents and then represents these in predicate logic. These algorithms also regenerate the original sentences from the representation in order to check the accuracy of representation. These algorithms have been tested on real text of English and Urdu. As the algorithms work on pre-tagged input files, so if the tagging is done correctly then these algorithms achieve high level of accurately. Therefore it is required that there should be proper rules with the help of which one can correctly tag the input text into phrases/constituents.

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Born in Swat, Khyber Pakhtunkhwa, Pakistan, the author did his Master in Computer Science from Gomal University, Pakistan & MS from University of Peshawar, Pakistan. He is currently faculty at the Department of Computer Science, University of Peshawar, Pakistan. The author regularly presents his research in International Conferences.

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