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Using GIPO to support learning in knowledge acquisition and automated planning

McCluskey, T.L. and Simpson, R.M. (2005) Using GIPO to support learning in knowledge acquisition and automated planning. In: The Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence - Workshop on Artificial Intelligence in Education, 12th-14th December 2005, Peterhouse College, Cambridge, UK.

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Abstract

The process of how knowledge is acquired and formulated in knowledge-intensive AI is difficult for a student to grasp without practical experience. Often, AI text books and lecture notes contain examples of logic formula or structured knowledge representations which are well refined and bug free. These polished examples are then used to show reasoning mechanisms or the execution of AI search methods. The process of how the knowledge representations themselves are acquired and validated is often neglected. In this paper we describe the use of a tool called GIPO for teaching AI students. GIPO helps students understand and integrate aspects of knowledge acquisition, knowledge engineering, automated planning and machine learning. We show how the tool’s features supports teaching and the student’s learning experience, and helps integrate the theory and practice in a range of AI and related subject areas.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
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Depositing User: Briony Heyhoe
Date Deposited: 29 Jan 2009 17:44
Last Modified: 22 Aug 2015 18:02
URI: http://eprints.hud.ac.uk/id/eprint/3247

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