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• W1880783585 abstract "Most current planners assume complete domain models and focus on generating correct plans. Unfortunately, domain modeling is a laborious and error-prone task, thus real world agents have to plan with incomplete domain models. While domain experts cannot guarantee completeness, often they are able to circumscribe the incompleteness of the model by providing annotations as to which parts of the domain model may be incomplete. In such cases, the goal should be to synthesize plans that are robust with respect to any known incompleteness of the domain. In this paper, we first introduce annotations expressing the knowledge of the domain incompleteness and formalize the notion of plan robustness with respect to an incomplete domain model. We then show an approach to compiling the problem of finding robust plans to the conformant probabilistic planning problem, and present experimental results with Probabilistic-FF planner." @default.
• W1880783585 created "2016-06-24" @default.
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• W1880783585 date "2013-12-05" @default.
• W1880783585 modified "2023-09-24" @default.
• W1880783585 title "Synthesizing Robust Plans under Incomplete Domain Models" @default.
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