Theory and algorithms for plan merging
Artificial Intelligence
Handling feature interactions in process-planning
Applied Artificial Intelligence - Special issue in artificial intelligence manufacturing, part 2
A Constraint Engine for Manufacturing Process Planning
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Case-based manufacturing process planning with integrated support for knowledge sharing
ISATP '95 Proceedings of the 1995 IEEE International Symposium on Assembly and Task Planning
An approach to a feature-based comparison of solid models of machined parts
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
AI planning versus manufacturing-operation planning: a case study
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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We have developed a domain-independent systematic methodology for plan merging at the various levels of plan abstraction. This method manifests itself in the hierarchical plan graph where each level contains a complete, partially merged plan. The principle advantage of this approach is that, once external interactions between nodes on a given level have been established, the continued merging of the plan fragments in one node can take place independently of plan fragments in other nodes on that level. This provides a decomposition or divide-and-conquer approach to plan merging. Another advantage to this decomposition approach is that replanning effort is minimized in the presence of the selection of alternative actions at some level of the hierarchical plan graph. Only those plan fragments which are in the same branch as the alternative selection need be considered for replanning. Also, an algorithm is proposed which takes a bilateral approach to breaking cyclic dependencies between nodes in the hierarchical plan graph. We demonstrate the utility of this hierarchical approach to plan merging through examples in the process planning domain.