The graph exploration problem asks a searcher to explore an unknown graph. This problem can be interpreted as the online version of the Traveling Salesman Problem. The treasure hunt problem is the corresponding online version of the shortest s-t-path problem. It asks the searcher to find a specific vertex in an unknown graph at which a treasure is hidden. Recently, the analysis of the impact of a priori knowledge is of interest. In graph problems, one form of a priori knowledge is a map of the graph. We survey the graph exploration and treasure hunt problem with an unlabeled map, which is an isomorphic copy of the graph, that is provided to the searcher. We formulate decision variants of both problems by interpreting the online problems as a game between the online algorithm (the searcher) and the adversary. The map, however, is not controllable by the adversary. The question is, whether the searcher is able to explore the graph fully or find the treasure for all possible decisions of the adversary. We prove the PSPACE-completeness of these games, whereby we analyze the variations which ask for the mere existence of a tour through the graph or path to the treasure and the variations that include costs. Additionally, we analyze the complexity of related problems that ask for a tour in the graph or a s-t path.
翻译:图形勘探问题要求搜索者探索未知的图表。 这个问题可以被解释为“ 旅行销售商问题” 的在线版本。 寻宝问题就是最短的 S- t路径问题的相应在线版本。 它要求搜索者在隐藏藏宝的未知图表中找到特定的顶点。 最近, 分析先验知识的影响是令人感兴趣的。 在图形中, 一种先验知识的形式是图图的地图。 我们用一张未标的地图来调查图的勘探和寻宝问题。 我们用一张未标的地图来调查图探索和寻宝问题, 这张地图是提供给搜索者的图表的无形态副本。 我们通过将在线问题解释为在线算法( 搜索者) 和对手之间的游戏来制定两个问题的决定变量。 但是, 地图无法被对手控制。 问题是, 搜索者能否充分探索图表, 或为对手的所有可能决定找到宝藏。 我们证明了这些游戏的完美性, 从而我们分析了这些游戏的变异性, 也就是我们仅仅要求通过图表路径或图解的变式, 包括我们想要的路径的变式。