Abstract
In this paper, we present a novel approach to flexible planning based on a two-stage paradigm of label member generation and solution extraction. The approach provides a new perspective on the flexible planning problem and speeds up the process of the problem solving in the artificial intelligence system plan. On the basis, we propose a novel algorithm based on label member by thoroughly exploring the structure of flexible planning graph, and apply the memorization strategy and heuristic information to prune the search space. The algorithm is provably sound, complete and polynomial-time and polynomial-space of label member generation. And the problems handled by the algorithm are more complex than the classical ones and much closer to the real world, which makes the solution plan safer. Else, because of wide application of intelligent planning, our research is very helpful to the development of artificial intelligent, robotology, intelligent agent, machine learning and so on.
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Proof. No propositions are labeled “i” in Step5, which is equal to that there are no new propositions generated in level i of the flexible planning graph, namely, the propositions in level i are the same as those in level i − 1. In addition, just because the propositions in level i and in level i − 1 are the same and mutexes are monotonically decreasing, proposition-proposition mutex relations can not increase in level i, which accordingly implies the actions that can be applied to the two levels are the same. Else, since proposition-proposition mutex set with label member “i − 1” is empty after Step6, the mutex relations do not decrease either, that is to say, the mutexes in level i are not changed. To sum up, the propositions, the mutexes and the actions of level i are identical with those of level i − 1. In fact, it is not hard to see that once two adjacent levels i − 1, i are identical, all future levels will be identical to i − 1 as well, so we can say the graph has been level off from level i − 1 on.
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Acknowledgement
This work described in this paper is partially supported by the Fundamental Research Funds for the Central Universities (3072020CFQ0602, 3072020CF0604, 3072020CFP0601) and 2019 Industrial Internet Innovation and Development Engineering (KY10600200021, KY10600200034).
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Xu, L., Jia, W., Li, Y., Shen, L. (2021). A Flexible Planning Approach Using Label Member. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12736. Springer, Cham. https://doi.org/10.1007/978-3-030-78609-0_30
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