Abstract: Given the prominence of AI planning in research and industry, the development of AI planning software and its integration into production architectures are becoming important. However, building and managing planning software is a complex and expertise-dependent process without methodological support that would ensure AI planning applications have high quality and industrial strength. To that end, we propose a lifecycle for developing AI planning systems that consists of ten phases related to the design, development, and operation of planning systems.
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