Skip to content
Preprint

Greedy approaches for Gold Grabbing on subclasses of split graphs

Aug 2026 · 0 citations · 7 references
Computer Science

TL;DR

It is proved that for complete split graphs $CS_{(2,n)}$, the greedy strategy yields a sequence of moves that maximizes the game value, contributing to a better understanding of the structural conditions that ensure the optimality of simple strategies in graph-based combinatorial games.

Abstract

The Gold Grabbing Game is a combinatorial game on vertex-weighted graphs in which two players alternately remove vertices while maintaining graph connectivity, aiming to maximize the total collected weight. Although the literature has primarily focused on strategies that guarantee victory, the question of optimality --- i.e., maximizing total gain --- remains less explored. In this work, we investigate the behavior of the greedy strategy in this setting. We show that this approach is not optimal for general split graphs, highlighting structural limitations of this class. On the other hand, we prove that for complete split graphs $CS_{(2,n)}$, the greedy strategy yields a sequence of moves that maximizes the game value. As a consequence, the first player does not lose when the number of vertices is even. These results contribute to a better understanding of the structural conditions that ensure the optimality of simple strategies in graph-based combinatorial games.

View source

Similar papers

Open access Jul 2026

Impartial Games on Graphs: Solving Kayles via Dynamic Programming and Periodicity Properties

This work considers combinatorial games in which two players alternately choose vertices from a finite graph until a winning condition is achieved, and focuses on the well-known game Kayles, in which the selected vertices must form an independent set and the player who makes the last valid move wins.

Marcos Felipe Medeiros-de-Souza, Felipe Eizo Hanada, F. Protti · 0 citations
Preprint Aug 2026

Chooser-Picker Degree Games for Regular Graphs

In the unbiased Chooser-Picker (also known as Client-Waiter) game played on the edge set of a graph, Picker offers a pair of unclaimed edges in each turn, Chooser claims one, and the remaining edge goes back to Picker. We study the Chooser-Picker (C-P) degree game played on $d$-regular graphs, where Chooser aims to max...

Lajos Gyõrffy · 1 citation
Preprint Aug 2026

Degree Game for Special Regular Graphs

The $d/4$ bound for some infinite graph families, such as the hypercube graph $Q_d$, grids and tori, is improved and it is shown that Breaker can secure a degree of one at every vertex in $Q_3$, then lifted to higher dimensions, where Breaker can guarantee a degree of at least $\lfloor d/3 \rfloor$.

Lajos Gyõrffy · 2 citations
Preprint Aug 2026

Cop numbers for subclasses of partial cubes

The game of Cops and Robbers is a classical pursuit--evasion game on graphs. For a graph $G$, the cop number $c(G)$ is the minimum number of cops needed to guarantee the capture of a robber on $G$. Although this parameter has been determined for several fundamental graph classes, comparatively few exact results are kno...

Zhaoman Huang, Yanping Xie, Shoujun Xu · 0 citations
Jul 2026

Structural Tractability Frontiers for Metric Repair

This paper asks what structural properties of the graph itself make metric repair tractable, and gives pseudo-polynomial time algorithms for series-parallel graphs, and by generalization, graphs of bounded treewidth and a new algorithm for the length-bounded multicut problem.

Asaf Etgar, A. Gilbert, Jamie Tucker-Foltz · 0 citations
Open access 2026

A BRANCH AND BOUND ALGORITHM FOR FINDING THE POSITIVE INFLUENCE DOMINATING SET ON CHORDAL GRAPHS

This paper develops an exact algorithm based on the Branch and Bound approach for solving PIDS on chordal graphs, which involves identifying the smallest group of vertices in a given network that maximizes influence throughout the network.

Y A Bekhti, M. Lalou, Méziane Aïder et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.