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Related papers: Strategic deployment in graphs

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We consider combinatorial problems that can be solved in polynomial time for graphs of bounded treewidth but where the order of the polynomial that bounds the running time is expected to depend on the treewidth bound. First we review some…

Data Structures and Algorithms · Computer Science 2015-03-19 Stefan Szeider

Given a directed graph $G=(V,A)$, the Directed Maximum Leaf Spanning Tree problem asks to compute a directed spanning tree (i.e., an out-branching) with as many leaves as possible. By designing a Branch-and-Reduced algorithm combined with…

Data Structures and Algorithms · Computer Science 2009-11-11 Daniel Raible , Henning Fernau

Training graph neural networks on large datasets has long been a challenge. Traditional approaches include efficiently representing the whole graph in-memory, designing parameter efficient and sampling-based models, and graph partitioning…

Machine Learning · Computer Science 2024-11-19 Dmytro Lopushanskyy , Borun Shi

Given a graph $G$, the NP-hard Maximum Planar Subgraph problem (MPS) asks for a planar subgraph of $G$ with the maximum number of edges. There are several heuristic, approximative, and exact algorithms to tackle the problem, but---to the…

Data Structures and Algorithms · Computer Science 2016-08-29 Markus Chimani , Karsten Klein , Tilo Wiedera

We generalise the popular cops and robbers game to multi-layer graphs, where each cop and the robber are restricted to a single layer (or set of edges). We show that initial intuition about the best way to allocate cops to layers is not…

Combinatorics · Mathematics 2026-02-10 Jessica Enright , Kitty Meeks , William Pettersson , John Sylvester

In this paper, we address the numerical solution of the Optimal Transport Problem on undirected weighted graphs, taking the shortest path distance as transport cost. The optimal solution is obtained from the long-time limit of the gradient…

Numerical Analysis · Mathematics 2020-09-29 Enrico Facca , Michele Benzi

The aim of this work is to develop a fully-distributed algorithmic framework for training graph convolutional networks (GCNs). The proposed method is able to exploit the meaningful relational structure of the input data, which are collected…

Machine Learning · Computer Science 2022-12-21 Simone Scardapane , Indro Spinelli , Paolo Di Lorenzo

The min-rank of a graph was introduced by Haemers (1978) to bound the Shannon capacity of a graph. This parameter of a graph has recently gained much more attention from the research community after the work of Bar-Yossef et al. (2006). In…

Combinatorics · Mathematics 2016-11-26 Son Hoang Dau , Yeow Meng Chee

It is required to find an optimal order of constructing the edges of a network so as to minimize the sum of the weighted connection times of relevant pairs of vertices. Construction can be performed anytime anywhere in the network, with a…

Data Structures and Algorithms · Computer Science 2021-04-20 Igor Averbakh

We study the m-eternal domination problem from the perspective of the attacker. For many graph classes, the minimum required number of guards to defend eternally is known. By definition, if the defender has less than the required number of…

Discrete Mathematics · Computer Science 2022-04-07 Václav Blažej , Jan Matyáš Křišťan , Tomáš Valla

In this work we introduce and study a pursuit-evasion game in which the search is performed by heterogeneous entities. We incorporate heterogeneity into the classical edge search problem by considering edge-labeled graphs: once a search…

Discrete Mathematics · Computer Science 2024-01-26 Dariusz Dereniowski , Łukasz Kuszner , Robert Ostrowski

We consider problems related to the combinatorial game (Free-)Flood-It, in which players aim to make a coloured graph monochromatic with the minimum possible number of flooding operations. We show that the minimum number of moves required…

Data Structures and Algorithms · Computer Science 2013-06-14 Kitty Meeks , Alexander Scott

We study the interplay between chip-firing games and potential theory on graphs, characterizing reduced divisors ($G$-parking functions) on graphs as the solution to an energy (or potential) minimization problem and providing an algorithm…

Combinatorics · Mathematics 2012-07-31 Matthew Baker , Farbod Shokrieh

Consider an agent exploring an unknown graph in search of some goal state. As it walks around the graph, it learns the nodes and their neighbors. The agent only knows where the goal state is when it reaches it. How do we reach this goal…

Data Structures and Algorithms · Computer Science 2023-01-02 Siddhartha Banerjee , Vincent Cohen-Addad , Anupam Gupta , Zhouzi Li

The multi-agent path finding (MAPF) problem asks to find a set of paths on a graph such that when synchronously following these paths the agents never encounter a conflict. In the most widespread MAPF formulation, the so-called Classical…

Multiagent Systems · Computer Science 2025-05-16 Artem Agafonov , Konstantin Yakovlev

We consider the problem of collectively delivering some message from a specified source to a designated target location in a graph, using multiple mobile agents. Each agent has a limited energy which constrains the distance it can move.…

Data Structures and Algorithms · Computer Science 2020-08-27 Andreas Bärtschi , Jérémie Chalopin , Shantanu Das , Yann Disser , Barbara Geissmann , Daniel Graf , Arnaud Labourel , Matúš Mihalák

Inspired by scenarios where the strategic network design and defense or immunisation are of the central importance, Goyal et al. [3] defined a new Network Formation Game with Attack and Immunisation. The authors showed that despite the…

Computer Science and Game Theory · Computer Science 2023-02-13 Carme Àlvarez , Arnau Messegué

Motivated by real-world applications such as the allocation of public housing, we examine the problem of assigning a group of agents to vertices (e.g., spatial locations) of a network so that the diversity level is maximized. Specifically,…

Data Structures and Algorithms · Computer Science 2024-04-02 Zirou Qiu , Andrew Yuan , Chen Chen , Madhav V. Marathe , S. S. Ravi , Daniel J. Rosenkrantz , Richard E. Stearns , Anil Vullikanti

We consider ordinal approximation algorithms for a broad class of utility maximization problems for multi-agent systems. In these problems, agents have utilities for connecting to each other, and the goal is to compute a maximum-utility…

Multiagent Systems · Computer Science 2017-11-30 Ben Abramowitz , Elliot Anshelevich

Graph neural networks (GNNs) have attracted increasing interests. With broad deployments of GNNs in real-world applications, there is an urgent need for understanding the robustness of GNNs under adversarial attacks, especially in realistic…

Machine Learning · Computer Science 2021-06-22 Jiaqi Ma , Junwei Deng , Qiaozhu Mei