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...

Introduction to the Project Planform is a 26 month long project with a planned starting date of October 1st, 1999. It will be led by Prof Lee McCluskey at University of Huddersfield, Ms Ruth Aylett at the University of Salford, and Dr Maria Fox and Dr Derek Long at the University of Durham. There will be three other post- doctoral members of the team, one at each of the three Universities. The project is funded by the EPSRC, but it also will be supported by the UK National Air Traffic Services Ltd, and CogSys Ltd. The total value of the project is estimated at around 400,000 pounds. Project Relevance Projects such as those sponsored by ARPI [1] and NASA [13] have shown that large-scale planning systems - such as SIPE-II and O-Plan - developed in research centres, can be cost effective. AI Planning systems such as these are domain-independent, that is, their algorithms and representational facilities are logically separate from the model of a particular applicat

Knowledge engineering for AI planning is the process that deals with the acquisition, validation and maintenance of planning domain models, and the selection and optimization of appropriate planning machinery to work on them. Evidence from the growing body of experience in applying planning technology suggests that knowledge engineering issues are crucial to an application 's success. The Knowledge Engineering Technical Co-ordination Unit of PLANET has been active for several years now in carrying out workshops and sponsoring cross-site visits on the subject. Here I briefly summarise some of the material in our roadmap doc- ument(McCluskey et al. 2000), selecting some of the important research questions from it, and introduce the papers that are to be presented in this workshop.