Pruning and Preprocessing Methods for Inventory-Aware Pathfinding

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 prepro-cessing 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.