Linear-Time Safe-Alternating DFS and SCCs
Abstract
An alternating graph is a directed graph whose vertex set is partitioned into two classes, existential and universal. This forms the basic arena for a plethora of infinite duration two-player games where Player~$\square$ and~$\ocircle$ alternate in a turn-based sliding of a pebble along the arcs they control. We study alternating strongly-connectedness as a generalization of strongly-connectedness in directed graphs, aiming at providing a linear time decomposition and a sound structural graph characterization. For this a refined notion of alternating reachability is introduced: Player~$\square$ attempts to reach vertices without leaving a prescribed subset of the vertices, while Player~$\ocircle$ works against. This is named \emph{safe alternating reachability}. It is shown that every arena uniquely decomposes into safe alternating strongly-connected components where Player~$\square$ can visit each vertex within a given component infinitely often, without having to ever leave out the component itself. Our main result is a linear time algorithm for computing this alternating graph decomposition. Both the underlying graph structures and the algorithm generalize the classical decomposition of a directed graph into strongly-connected components. The algorithm builds on a linear time generalization of the depth-first search on alternation, taking inspiration from Tarjan 1972 machinery. Our theory has direct applications in solving well-known infinite duration pebble games faster. Dinneen and Khoussainov showed in 1999 that deciding a given Update Game costs $O(mn)$ time, where $n$ is the number of vertices and $m$ is that of arcs. We solve the task in $\Theta(m+n)$ linear~time. The complexity of Explicit McNaughton-Müller Games also improves from cubic to quadratic.
- Publication:
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arXiv e-prints
- Pub Date:
- October 2016
- DOI:
- 10.48550/arXiv.1610.09679
- arXiv:
- arXiv:1610.09679
- Bibcode:
- 2016arXiv161009679C
- Keywords:
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- Computer Science - Data Structures and Algorithms