Exploration of High-Dimensional Grids by Finite State Machines

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Stefan Dobrev, Lata Narayanan, Jaroslav Opatrny, Denis Pankratov
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引用次数: 0

Abstract

We consider the problem of finding a “treasure” at an unknown point of an n-dimensional infinite grid, \(n\ge 3\), by initially collocated finite automaton (FA) agents. Recently, the problem has been well characterized for 2 dimensions for deterministic as well as randomized FA agents, both in synchronous and semi-synchronous models (Brandt et al. in Proceedings of 32nd International Symposium on Distributed Computing (DISC) LIPCS 121:13:1–13:17, 2018; Emek et al. in Theor Comput Sci 608:255–267, 2015). It has been conjectured that \(n+1\) randomized FA agents are necessary to solve this problem in the n-dimensional grid (Cohen et al. in Proceedings of the 28th SODA, SODA ’17, pp 207–224, 2017). In this paper we disprove the conjecture in a strong sense: we show that three randomized synchronous FA agents suffice to explore an n-dimensional grid for any n. Our algorithm is optimal in terms of the number of the agents. Our key insight is that a constant number of FA agents can, by their positions and movements, implement a stack, which can store the path being explored. We also show how to implement our algorithm using: four randomized semi-synchronous FA agents; four deterministic synchronous FA agents; or five deterministic semi-synchronous FA agents. We give a different, no-stack algorithm that uses 4 deterministic semi-synchronous FA agents for the 3-dimensional grid. This is provably optimal in the number of agents and the exploration cost, and surprisingly, matches the result for 2 dimensions. For \(n\ge 4\), the time complexity of the stack-based algorithms mentioned above is exponential in distance D of the treasure from the starting point of the agents. We show that in the deterministic case, one additional finite automaton agent brings the time down to a polynomial. We also show that any algorithm using 3 synchronous deterministic FA agents in 3 dimensions must travel beyond \(\Omega (D^{3/2})\) from the origin. Finally, we show that all the above algorithms can be generalized to unoriented grids. More specifically, six deterministic semi-synchronous FA agents are sufficient to locate the treasure in an unoriented n-dimensional grid.

Abstract Image

用有限状态机探索高维网格
摘要 我们考虑的问题是在一个 n 维的无限网格中,通过最初的有限自动机(FA)代理在一个未知点找到一个 "宝藏"。最近,对于确定性以及随机化的 FA 代理,该问题在同步和半同步模型中的两个维度都得到了很好的描述(Brandt 等人,发表于第 32 届分布式计算国际研讨会论文集(DISC)LIPCS 121:13:1-13:17, 2018;Emek 等人,发表于 Theor Comput Sci 608:255-267, 2015)。有人猜想,要在 n 维网格中解决这个问题,必须要有\(n+1\) 个随机 FA 代理(Cohen 等人,载于第 28 届 SODA 会议论文集,SODA '17, 第 207-224 页,2017 年)。在本文中,我们从强意义上反证了这一猜想:我们证明,对于任意 n,三个随机同步 FA 代理足以探索 n 维网格。我们的主要见解是,恒定数量的 FA 代理可以通过其位置和移动实现堆栈,从而存储正在探索的路径。我们还展示了如何使用以下方法实现我们的算法:四个随机半同步 FA 代理;四个确定性同步 FA 代理;或五个确定性半同步 FA 代理。我们给出了一种不同的无堆栈算法,即在三维网格中使用 4 个确定性半同步 FA 代理。这种算法在代理数量和探索成本上都是最优的,而且令人惊讶的是,它与二维网格的结果相吻合。对于 \(n\ge 4\) ,上述基于堆栈的算法的时间复杂度是宝藏与代理起点距离 D 的指数。我们证明,在确定性情况下,多一个有限自动机代理就能把时间降到多项式。我们还证明,任何在 3 维空间中使用 3 个同步确定性有限自动机代理的算法都必须从原点出发超过 \(\Omega (D^{3/2})\)。最后,我们证明上述所有算法都可以推广到无定向网格。更具体地说,六个确定性半同步 FA 代理足以在无方向的 n 维网格中找到宝藏。
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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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