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Pruning and preprocessing methods for inventory-aware pathfinding

机译:清单感知路径灌注的修剪和预处理方法

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Inventory-Aware Pathfinding is concerned with finding paths while taking into account that picking up items, e.g., keys, allow the character to unlock blocked pathways, e.g., locked doors. In this work we present a pruning method and a preprocessing method that can improve significantly the scalability of such approaches. We apply our methods to the recent approach of Inventory-Driven Jump-Point Search (InvJPS). First, we introduce InvJPS+ that allows to prune large parts of the search space by favoring short detours to pick up items, offering a trade-off between efficiency and optimality. Second, we propose a preprocessing step that allows to decide on runtime which items, e.g., keys, are worth using thus pruning potentially unnecessary items before the search starts. We show results for combinations of the pruning and preprocessing methods illustrating the best choices over various scenarios.
机译:清单感知路径查找涉及查找路径,同时考虑到拾取项目,例如键,允许字符解锁阻塞路径,例如锁定门。在这项工作中,我们提出了一种修剪方法和预处理方法,可以显着提高这种方法的可扩展性。我们将我们的方法应用于最近的库存驱动的跳跃点搜索(INVJPS)的方法。首先,我们介绍了Invjps +,它可以通过青少年绕道来拾取物品来修剪搜索空间的大量部分,在效率和最优性之间提供权衡。其次,我们提出了一种预处理步骤,允许在搜索开始之前决定哪些项目,例如键的运行时值得使用潜在不必要的项目。我们展示了修剪和预处理方法的结果,说明了各种场景的最佳选择。

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