Plan reuse versus plan generation: a theoretical and empirical analysis
Artificial Intelligence - Special volume on planning and scheduling
Fast planning through greedy action graphs
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Extending Planning Graphs to an ADL Subset
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
The detection and exploitation of symmetry in planning problems
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Replanning in a Resource-Based Framework
Proceedings of the 9th ECCAI-ACAI/EASSS 2001, AEMAS 2001, HoloMAS 2001 on Multi-Agent-Systems and Applications II-Selected Revised Papers
Lifelong Planning for Mobile Robots
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
Lagrange Multipliers for Local Search on Planning Graphs
ECAI '00 Proceedings of the Workshop on Local Search for Planning and Scheduling-Revised Papers
Kernel functions for case-based planning
Artificial Intelligence
| Hi-index | 0.00 |
Fast plan adaptation is important in many AI applications requiring a plan management module. From a theoretical point of view, in the worst case plan adaptation is no more efficient than a complete regeneration of the plan. However, in practice adapting an existing plan can be much more efficient than generating a new one from scratch, especially when the changes to the plan that are required concern only some circumscribed parts of the plan. In this paper we discuss a simple plan-adaptation method based on Blum and Furst's Planning Graphs approach. The method is domain-independent and exploits the planning graph structure for a fast identification of the flaws that are present in the plan, and for fixing them by replanning limited portions of the plan. We present results from some experiments aimed at testing our method with several modifications of planning problems that are hard to solve for current planners based on planning graphs, such as IPP, Graphplan, and Blackbox. These results show that the method in practice is very efficient, especially when the plan can be adapted by changes that are localized in restricted parts of the original plan.