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Investigation into the Theoretical Properties of, and the Relationship Between, AI Planning Domain Models.

Shoeeb, Salihin (2012) Investigation into the Theoretical Properties of, and the Relationship Between, AI Planning Domain Models. Technical Report. University of Huddersfield, Huddersfield, UK. (Unpublished)

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      Abstract

      Over the past decade, there have been substantial advances in knowledge representation (KR)
      techniques for AI planning. Typically, planners search a space of solution to find a suitable
      and most accurate sequence of actions to achieve a specific task from a set of initial and goal
      states. However, the progress in this field still cannot cope with the ever increasing of the
      complexities of modern systems, which makes knowledge representation an expensive and
      error prone process. Planning is considered as one of artificial intelligence fields where
      knowledge representation (KR) is extremely critical. However, a little work has been aimed
      at “measuring” domain models; the aim of this research is to develop a set of criteria and
      metrics to assess the accruing and complexity of a particular classical planning problem
      domain model. To reach that point the system has to have enough knowledge and knowledge
      has to be well represented for the problem at hand. In this report, we have outlined the
      prototype the system and design planning domain model metric tools.
      1.2 Introduction

      Item Type: Monograph (Technical Report)
      Subjects: Q Science > QA Mathematics > QA76 Computer software
      Schools: School of Computing and Engineering
      Related URLs:
      Depositing User: Salihin Shoeeb
      Date Deposited: 06 Mar 2012 13:42
      Last Modified: 07 Mar 2012 01:38
      URI: http://eprints.hud.ac.uk/id/eprint/12907

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