AI planning versus manufacturing-operation planning: a case study

  • Authors:

  • Dana S. Nau;Satyandra K. Gupta;William C. Regli

  • Affiliations:

  • Computer Science Department and Institute for Systems Research, University of Maryland, College Park, MD;Robotics Institute, Carnegie Mellon University, Pittsburgh, PA;Computer Science Department and Institute for Systems Research, University of Maryland, College Park, MD and National Institute of Standards and Technology, Manufacturing Systems Integration Divis ...

  • Venue:
  • IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1995

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Abstract

Although AI planning techniques can potentially be useful in several manufacturing domains, this potential remains largely unrealized. In order to adapt AI planning techniques to manufacturing, it is important to develop more realistic and robust ways to address issues important to manufacturing engineers. Furthermore, by investigating such issues, AI researchers may he able to discover principles that are relevant for AI planning in general. As an example, in this paper we describe the techniques for manufacturing-operation planning used in IMACS (Interactive Manufacturability Analysis and Critiquing System), and compare and contrast them with the techniques used in classical AI planning systems. We describe how one of IMACS's planning techniques may be useful for AI planning in general--and as an example, we describe how it helps to explain a puzzling complexity result in AI planning.