On the Robustness of Domain-Independent Planning Engines: The Impact of Poorly-Engineered Knowledge
On the Robustness of Domain-Independent Planning Engines: The Impact of Poorly-Engineered Knowledge
复制标题
关于与领域无关的规划引擎的鲁棒性：设计不良的知识的影响
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
L. Chrpa
中科院分区：
文献类型：
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作者：
M. Vallati;L. Chrpa
自动规划的最新进展正在导致规划引擎在广泛的实际应用中的使用。随着应用程序中规划技术的利用增加，评估规划引擎对于作为推理过程输入的设计不良（或恶意修改）知识模型的鲁棒性变得势在必行。在这项工作中，要了解规划引擎的工程知识的影响，我们考虑的角度来看，一个假设的攻击者，有兴趣巧妙地操纵这些知识，引入不必要的开销，从而减缓规划过程。这种叙事策略使我们能够描述无法通过模型验证检测到的不同类型的知识工程问题，并测量它们对一系列规划引擎的性能的影响，这些规划引擎利用非常不同的方法进行预处理和搜索等步骤。
Recent advances in automated planning are leading towards the use of planning engines in a wide range of real-world applications. As the exploitation of planning techniques in applications increases, it becomes imperative to assess the robustness of planning engines with regards to poorly-engineered (or maliciously modified) knowledge models provided as input for the reasoning process. In this work, to understand the impact of poorly-engineered knowledge on planning engines, we consider the perspective of a hypothetical attacker that is interested in subtly manipulating such knowledge to introduce unnecessary overheads that consequently slow down the planning process. This narrative ploy allows us to describe different types of knowledge engineering issues that cannot be detected via validation of the models, and to measure their impact on the performance of a range of planning engines exploiting very different approaches for steps like pre-processing and search.
基于计划的高效多电池负载管理策略
影响因子：
5
作者：
Fox M
通讯作者：
Fox M