Despite the progress in automated planning and scheduling systems, these systems still need to be fed by carefully engineered domain and problem descriptions and they need to be fine-tuned for particular domains and problems. Knowledge engineering for AI planning and scheduling deals with the acquisition, design, validation, and maintenance of domain models, as well as the selection and optimization of appropriate machinery to work on them. These processes directly influence the success of real-world planning and scheduling applications. The importance of knowledge engineering techniques is clearly demonstrated by the performance gap between domain-independent planners and planners that exploit domain-specific knowledge.

This workshop continues the tradition of several International Competitions on Knowledge Engineering for Planning and Scheduling (ICKEPS) and previous KEPS workshops. While ICKEPS primarily focuses on software tools and domain encoding techniques, this workshop covers all aspects of knowledge engineering for AI planning and scheduling.