Planform: An Open Environment for Building Planners 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, Ruth Aylett at the University of Salford, and Dr Maria Fox and Dr Derek Long at the University of Durham. Prof McCluskey will take responsibility for the management of the overall project. The project is funded by the EPSRC, but it also will be supported by the UK National Air Traffic Services Ltd, and CogSys Ltd.
Projects such as those sponsored by ARPI and NASA 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 application domain. These systems have been criticised, however, for their theoretical opacity and lack of a sound logical basis. Construction of the domain model needed for an application has been shown in practice to be very slow and laborious, requiring expertise not only in the applications domain but in the detailed working of the planning system. It is generally agreed that the 'hand-crafted' approach to domain model construction currently in use must be replaced by stronger and more consistent methods which can compete successfully with more conventional approaches in terms of software lifecycle costs.
A related methodological problem is the difficulty of validating research claims based on empirical evidence gathered from the application of planning algorithms to domain models. While there are commonly used applications for testing planners, and some syntactic conventions and `standard' domain languages, there are, as yet, no precise planning ontologies that would provide a medium for exchange in the AI Planning community.
Aims and objectives
We aim to research, develop and evaluate a method and supporting high level research platform for the systematic construction of planner domain models and abstract specifications of planning algorithms, and their automated synthesis into sound, efficient programs that generate and execute plans. Our objectives are to:
The three universities involved in this project have an excellent record in automated planning research, and form an internationally competitive team.