Abstract
In this paper we present an overview of the principle components of GIPO, an environment to support knowledge acquisition for AI Planning. GIPO assists in the knowledge formulation of planning domains, and in prototyping planning problems within these domains. GIPO features mixed-initiative components such as generic type composition, an operator induction facility, and various plan animation and validation tools. We outline the basis of the main tools, and show how an engineer might use them to formulate a domain model. Throughout the paper we illustrate the formulation process using the Hiking Domain.
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McCluskey, T.L., Simpson, R.M. (2004). Knowledge Formulation for AI Planning. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds) Engineering Knowledge in the Age of the Semantic Web. EKAW 2004. Lecture Notes in Computer Science(), vol 3257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30202-5_30
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DOI: https://doi.org/10.1007/978-3-540-30202-5_30
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