Early work on the NONLIN and O-Plan projects indicated a need for a defined methodology which would guide users performing various roles in the acquisition and analysis of domain requirements for planning. This work included links to a requirement analysis methodology, CORE (COntrolled Requirements Expression) , tool support via an intelligent assistant as part of the Task Formalism (TF) Workstation and an initial collection of guidelines and checklists to aid in using the TF domain description language. This paper describes work underway to follow-on from this past research and to infuse it with knowledge gained from recent research related to planning domain development, knowledge modelling, design rationale and ontological and requirements engineering. Introduction The activities involved in discovering, engineering, documenting, and maintaining a set of domain constructs for most AI planning-based projects can be considered ad hoc and disorganised, at best. The current sources for...

Process engineering involves a search for new models of organising work. This synthesis task can become quite difficult and time-consuming as the amount of detail required and interactions between activities increases. Domain independent AI planning offers some promising techniques and representations to assist in this effort. One of the major impediments to transferring this technology to applied, real-world settings is the difficulty encountered in building the domain model which is used in the automated generation of these plans. Competence, as well as good tools, is necessary to carry out this task. A plan domain methodology should be available which provides structured organisational development activities. Users need to know what tasks they have to perform: for each step, information must be available about what input will be needed, and what output will be required, what is to be done and how it can be done well. This paper presents the Common Process Methodology (CPM) which aim...

To develop a quality Hierarchical Task Network (HTN) planning application, one must understand how to use the representational devices provided by these systems to construct a principled model of an application domain. Support for this objective is currently limited to evolving guidance frameworks and repositories of domain descriptions. To date, there has been no description of the application of these guidance frameworks to form concrete domain descriptions. The developer is instead left to discover for themself the mapping between the steps of the frameworks and entries in the repositories. In this paper, we address this issue by describing the development of a HTN solution for the construction industry with the guidance of the TF Method. From this experience, we conclude that the TF Method offers significant assistance to the knowledge engineer. Specifically, the method highlights the importance of a planned approach to the development of an application, a conscious commit...

We present a compilation-based approach to reducing the representational distance between application domain experts and AI planning technology. The approach combines a representation designed to match the structure of human expertise in the construction industry with an established planning technique. The design of this representation is derived from a study carried out with experts in the industry. This study shows that expertise in the industry is centred on the components of a building and organised into a subcomponent structure. We demonstrate by encoding the results of this study into a HTN formalism that such formalisms fragment expert knowledge. This fragmentation leads to a large representational distance between expert and formalism, making the task of encoding and maintaining a planner knowledge base a complex one. Our solution is to provide a representation designed around the modelling requirements of the construction industry and then to compile HTN sche...