No matter how efficient or powerful Planning and Scheduling (P&S) engines are, they are only as good as the application knowledge that they use. If the P&S domain model is flawed, the resulting P&S application will be flawed.

The aims of the Knowledge Engineering (KE) Competition are to

• promote the knowledge-based and domain modeling aspects of P&S
• accelerate knowledge engineering research in AI P&S
• encourage the development and sharing of prototype tools or software platforms that promise more rapid, accessible, and effective ways to construct reliable and efficient P&S systems

KE for AI Planning has been defined as "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. Hence, knowledge engineering processes support the planning process: they comprise all of the off-line, knowledge-based aspects of planning that are to do with the application being built, and any on-line processes that cause changes in the planner's domain model". We expect the competition to encourage the development of tools across the whole KE area including domain modeling, heuristic acquisition, planner-domain matching, domain knowledge validation and so forth.

If the competition continues in the future we hope it will lead to some form of shared or communication languages or media for knowledge-based domain models. We hope that it will complement the current International Planning Competition held every 'odd' year at ICAPS.

Roman Barták and Lee McCluskey

ICAPS 2005