Safe Exploration of Arbitrary Dynamic Dangerous Networks

📅 2026-09-17
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
本文研究了动态危险网络中安全探索问题,通过设计算法使代理在无先验知识情况下也能探索所有安全节点并避免陷入黑洞。
📝 Abstract
Given a team of agents on the nodes of a graph-based network, the exploration problem requires each node to be visited by at least one agent. In the classical distributed setting of static networks, agents do not know the topology of the network; in the more recently investigated setting of dynamic networks, they may have prior knowledge about the graph class (e.g., trees, tori, rings) or other parameters (e.g., number of nodes). Gotoh et al. (2021) are the first to study the exploration problem of arbitrary dynamic networks, under the necessary minimal assumption that any two nodes will be connected by a temporal path infinitely often (temporal connectivity assumption). In this paper, we extend their study of exploration under temporal connectivity by considering dangerous dynamic networks, i.e., containing possibly one or more black holes. Whenever an agent enters a black hole, it will be trapped forever. The safe exploration problem requires a team to explore all the safe nodes, ensuring that at least one agent will never be trapped in a black hole. We first prove that, given the necessary (and sufficient) number of agents, a team of oblivious agents can perpetually explore the safe nodes without any prior knowledge of the network or the team, without agent or node IDs, under semi-synchronous schedulers. Then, we provide an algorithm that enables agents to safely explore the network and terminate. In this case, agents are equipped with unique IDs and persistent memory, and they know the number of safe nodes. Yet, in both cases, we prove that it is impossible for a team of agents on dynamic networks to correctly mark only the ports leading to black holes.
Problem

Research questions and friction points this paper is trying to address.

Dynamic Networks
Safe Exploration
Black Holes
Innovation

Methods, ideas, or system contributions that make the work stand out.

safe exploration
dynamic networks
black holes
oblivious agents
semi-synchronous schedulers
🔎 Similar Papers
2024-02-09IEEE Transactions on Automatic ControlCitations: 4