Abstract
Project management is a business process for successfully delivering one-of-a kind products and services under real-world time and resource constraints. Developing a project plan, a crucial element of project management, is a difficult task that requires significant experience and expertise. Interestingly, artificial intelligence researchers have developed both mixed-initiative and automated hierarchical planning systems for reducing planning effort and increasing plan evaluation measures. However, they have thus far not been used in project planning, in part because the relationship between project planning and hierarchical planning has not been established, hi this chapter, we identify this relationship and explain how project planning representations called work breakdown structures (WBS) are similar to plan representations employed by hierarchical planners. We exploit this similarity and apply well-known hierarchical planning techniques, including an integrated (case-based) plan retrieval module, to assist a project planner efficiently create WBSs. Our approach uses stored episodes (i.e., cases) of previous project planning experiences to support the development of new plans. We present an architecture for knowledge-based project planning system that implements this approach.
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Muñoz-Avila, H., Gupta, K., Aha, D.W., Nau, D. (2002). Knowledge-Based Project Planning. In: Dieng-Kuntz, R., Matta, N. (eds) Knowledge Management and Organizational Memories. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0947-9_11
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DOI: https://doi.org/10.1007/978-1-4615-0947-9_11
Publisher Name: Springer, Boston, MA
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