The authors introduce the problem of partially ordered top-quality planning, which allows specifying a subset of actions whose ordering in the plan is important. This interpolates between the two extremes of considering all orders important (top-quality planning) or all orders unimportant (unordered top-quality planning).
The motivation behind this new problem is threefold:
The authors propose three computational approaches to solve this new problem:
The authors prove the necessary theoretical guarantees for safe pruning and the use of partial order reduction in the proposed approaches. They also provide an experimental evaluation demonstrating the benefits of exploiting such techniques in this setting.
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by Michael Katz... um arxiv.org 04-03-2024
https://arxiv.org/pdf/2404.01503.pdfTiefere Fragen