Object-Centered Planning: Lifting Classical Planning from the Literal Level to the Object Level

Lee McCluskey, D. E. Kitchin, J. M. Porteous

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

A great deal of emphasis in classical AI planning research has been placed on search-control issues in plan generation, while the issue of knowledge representation and acquisition of models for use with classical planning engines has been largely ignored. Work in knowledge-based planning, on the other hand, is often associated with `scruffy' AI, there being no standard representation languages with associated formal semantics for encoding domain models. In this paper we describe a method to create a planning domain model which preserves the domain independence, generality and `clean' properties of generative planners to which the model can be attached. Our method is based on lifting the level of domain representation from the literal-centred, to the object-centred. This object-centred method has the advantage that it naturally allows for the creation of a supporting tools environment to help in (i) the creation and validation of a precise planning model, and (ii) the speed-up of plan generation.

LanguageEnglish
Pages346-353
Number of pages8
JournalProceedings of the International Conference on Tools with Artificial Intelligence
Publication statusPublished - Dec 1996

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Planning
Knowledge acquisition
Knowledge representation
Semantics
Engines

Cite this

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