A black hole in a graph is a dangerous site that disposes any incoming agent into that node without leaving any trace of its existence. In the Black Hole Search (BHS) problem, the goal is for at least one agent to survive, locate the position of the black hole, and then terminate. This problem has been extensively studied for static graphs, where the edges do not disappear with time. In dynamic graphs, where the edges may disappear and reappear with time, the problem has only been studied for specific graphs such as rings and cactuses. In this work, we investigate the problem of BHS for general graphs with a much weaker model with respect to the one used for the cases of rings and cactus graphs{bhattacharya_2023, Paola_2024}. We consider two cases: (a) where the adversary can remove at most one edge in each round, and (b) where the adversary can remove at most f edges in each round. In both scenarios, we consider rooted configuration. In the case when the adversary can remove at most one edge from the graph, we provide an algorithm that uses 9 agents to solve the BHS problem in O(m²) time given that each node v is equipped with O(log δᵥ) storage in the form of a whiteboard, where m is the number of edges in G and δᵥ is the degree of node v. We also prove that it is impossible for 2δBH many agents with O(log n) memory to locate the black hole where δBH is the degree of the black hole even if the nodes are equipped with whiteboards of O(log δᵥ) storage. In a scenario where the adversary can remove at most f edges and the initial configuration is rooted, we present an algorithm that uses $6f$ agents to solve the BHS problem. We also prove that solving BHS using $2f+1$ agents starting from a rooted configuration on a general graph is impossible, even with unlimited node storage and infinite agent memory.
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Kaur et al. (2024) studied this question.
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