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Incremental Contingency Planning for Recovering from Uncertain Outcomes

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Advances in Artificial Intelligence (CAEPIA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9868))

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Abstract

Incremental Contingency Planning is a framework that considers all potential failures in a plan and attempts to avoid them by incrementally adding contingency branches to the plan in order to improve the overall probability. The planner focuses its attempts on the higher probability outcomes. Precautionary planning is a form of incremental contingency planning that takes advantage of the speed of replanning for easy contingencies and only considers the unrecoverable outcomes in the plan. In this work, we present an approach to incrementally generating contingency branches to deal with uncertain outcomes. The main idea is to first generate a high probability non-branching seed plan, which is then augmented with contingency branches to handle the most critical outcomes. Any remaining outcomes are handled by runtime replanning.

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Notes

  1. 1.

    CPE is essentially the same as CCE [3], but expressed in terms of probability instead of in terms of cost.

References

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Acknowledgments

This work was supported by the NASA Safe Autonomous Systems Operations (SASO) project, the MINECO project EphemeCH TIN2014-56494-C4-4-P, and UAH project 2015/00297/001.

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Correspondence to Yolanda E-Martín .

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E-Martín, Y., R-Moreno, M.D., Smith, D.E. (2016). Incremental Contingency Planning for Recovering from Uncertain Outcomes. In: Luaces , O., et al. Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science(), vol 9868. Springer, Cham. https://doi.org/10.1007/978-3-319-44636-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-44636-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44635-6

  • Online ISBN: 978-3-319-44636-3

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