双内存模型中的树探索

Dominik Bojko, Karol Gotfryd, D. Kowalski, Dominik Pajak
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摘要

研究了基于确定性移动智能体的在线树探索问题。我们的主要目标是建立移动代理模型和环境的哪些特征允许线性探索时间。我们研究那些在进入一个节点时,不接收其进入的边作为输入的代理。在这种模型中,确定性的无内存探索是不可行的,因此需要允许代理使用一些内存。内存可以位于代理或每个节点上。现有的下界表明,如果内存仅在智能体上或仅在节点上,则探索需要超线性时间。我们展示了双内存模型中的树探索,当两个附加特征之一存在时,在线性时间内,代理具有恒定的内存和每个节点的对数度是可能的:每个节点的内存的固定初始状态(所谓的干净内存)或单个可移动令牌。在这两种模型中,我们给出了在线性时间内对任意树工作的两种算法。另一方面,在我们的下界中,我们表明,如果代理具有单个内存,并且每个节点上都有一个内存,那么即使在路径上,如果节点上的初始内存可以任意设置(即所谓的脏内存),则探索可能需要二次时间。这表明,拥有干净的节点内存或标记可以在双内存模型中对树进行线性时间探索,但没有这两种特征可能导致即使在简单路径上也需要二次探索时间。在可行性方面,我们证明了使用(渐近的)最小内存在尽可能小的线性时间内完成树探索是可能的。我们在CleanMem和Token模型中展示了两种算法,如果在代理上有恒定内存,在每个节点上有对数内存,则在最佳时间O (n)内探索任意未知树。我们的研究结果表明,在双内存模型的树探索背景下,关于节点清洁(固定)初始状态的假设可以“交易”为令牌。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tree exploration in dual-memory model
We study the problem of online tree exploration by a deterministic mobile agent. Our main objective is to establish what features of the model of the mobile agent and the environment allow linear exploration time. We study agents that, upon entering a node, do not receive as input the edge via which they entered. In such model, deterministic memoryless exploration is infeasible, hence the agent needs to be allowed to use some memory. The memory can be located at the agent or at each node. The existing lower bounds show that if the memory is either only at the agent or only at the nodes, then the exploration needs superlinear time. We show that tree exploration in dual-memory model, with constant memory at the agent and logarithmic in the degree at each node is possible in linear time when one of the two additional features is present: fixed initial state of the memory at each node (so called clean memory) or a single movable token. We present two algorithms working in linear time for arbitrary trees in these two models. On the other hand, in our lower bound we show that if the agent has a single bit of memory and one bit is present at each node, then the exploration may require quadratic time even on paths, if the initial memory at nodes could be set arbitrarily (so called dirty memory). This shows that having clean node memory or a token allows linear time exploration of trees in the dual-memory model, but having neither of those features may lead to quadratic exploration time even on a simple path. of the on feasibility of we show that is possible to complete the tree exploration in the minimum possible linear time using (asymptotically) minimal memory. We show two algorithms in models CleanMem and Token , exploring arbitrary unknown trees in the optimal time O ( n ) if constant memory is located at the agent and logarithmic memory is located at each node. Our results show that in the context of tree exploration in dual-memory model, the assumption about clean (fixed initial state of node can be “traded” for a token.
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