This paper postulates a rigorous method for the construction of classical planning domain models. We describe, with the help of a non-trivial example, a tool supported method for encoding such models. The method results in an `object-centred' specification of the domain that lifts the representation from the level of the literal to the level of the object. Thus, for example, operators are defined in terms of how they change the state of objects, and planning states are defined as amalgams of the objects' states. The method features two classes of tools: for initial capture and validation of the domain model; and for operationalising the domain model (a process we call compilation) for later planning. Here we focus on compilation tools used to generate macros and goal orders to be utilised at plan generation time. We describe them in depth, and evaluate empirically their combined benefits in plan-generation speed-up. The method's main benefit is in helping the modeller to pro...

Our research concerns formal, expressive, objectcentred languages and tools for use in engineering domains for planning applications. In this paper we extend our recent work on an object-centred language for encoding precondition planning domains to a language called OCL h , designed for HTN planning. Domain encodings for HTN planners are particularly troublesome, because they tend to be used in knowledged-based applications requiring a great deal of `domain engineering', and the abstract operators central to an HTN model do not share the fairly clear declarative semantics of concrete pre- and post condition operators. Central to our approach is the development, in parallel, of the abstract operator set and the hierarchical state specification of the objects that the operators manipulate. In this paper we define and illustrate a transparency property, together with a transparency checking tool, which helps the developer to encode a clear planning model in OCL h . Our encoding of the Tr...

This paper describes inputs to various international standardisation efforts for process and plan interchange. Our approach takes a top down perspective. It seeks to add the small but vital overview that can sit above the detailed representations or ontologies already available. It seeks to provide a framework within which alternative detailed ontologies can be created and evaluated in use. The contribution of this paper is to propose a structure for a plan ontology which isintended to allow for the progressive definition of the various components in a way which should increase the prospect of achieving a smooth fit of the various components into the whole.

In this paper we argue generally for a move to an object-centred formulation of precondition planning. Our previous work has demonstrated some of the advantages of systematically creating and compiling an object-centred domain model. Here we describe a complementary object-centred planning engine which exploits such a domain model, and review some of its benefits. We also survey related work that has attempted to exploit the object-oriented approach in planning. 1 Introduction Much AI planning research has concentrated on the design, analysis and efficiency of planning algorithms, with relatively little attention being paid to the creation and capture of planning domain models. Representational issues can have a big impact on planner performance. For example, it has been shown that different encodings of the same problem domain used with the same planner can give different results [9]. The construction of planning domain models is an important issue in AI planning, especially if we wi...