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Gathering Teams of Deterministic Finite Automata on a Line

Authors Younan Gao , Andrzej Pelc

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Author Details

Younan Gao
  • Department of Computer Science, University of Milano-Bicocca, Italy
Andrzej Pelc
  • Université du Québec en Outaouais, Gatineau, Canada

Funding

  • Gao, Younan: Partially supported by the Research Chair in Distributed Computing at the Université du Québec en Outaouais and MUR 2022YRB97K, PINC, Pangenome Informatics: from Theory to Applications.
  • Pelc, Andrzej: Partially supported by NSERC discovery grant RGPIN-2024-03767 and by the Research Chair in Distributed Computing at the Université du Québec en Outaouais.

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Younan Gao and Andrzej Pelc. Gathering Teams of Deterministic Finite Automata on a Line. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 11:1-11:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.OPODIS.2024.11

Abstract

Several mobile agents, modelled as deterministic finite automata, navigate in an infinite line in synchronous rounds. All agents start in the same round. In each round, an agent can move to one of the two neighboring nodes, or stay idle. Agents have distinct labels which are integers from the set {1,…,L}. They start in teams, each of which consists of x agents, for some fixed integer x. Agents in a team have the same starting node. The adversary decides the compositions of teams, and their starting nodes. Whenever an agent enters a node, it sees the entry port number and the states of all collocated agents; this information forms the input of the agent on the basis of which it transits to the next state and decides the current action. The aim is for all agents to gather at the same node and stop. Gathering is feasible, if this task can be accomplished for any decisions of the adversary, and its time is the worst-case number of rounds from the start till gathering.
We consider the feasibility and time complexity of gathering teams of agents, and give a complete solution of this problem. It turns out that both feasibility and complexity of gathering depend on the crucial parameter x which is the size of teams. For the oriented line, gathering is impossible if x = 1, and it can be accomplished in time O(D), for x > 1, where D is the distance between the starting nodes of the most distant teams. This complexity is of course optimal. For the unoriented line, the situation is different. For x = 1, gathering is also impossible, but for x = 2, the optimal time of gathering is Θ(Dlog L), and for x ≥ 3 the optimal time of gathering is Θ(D).
Solving the gathering problem for agents that are finite automata navigating in an infinite environment requires new methodological tools. Traditional gathering techniques in graphs are count driven: agents make decisions based on counting steps. Since distances between agents may be unbounded, agents have to count unbounded numbers of steps. When agents are finite automata, counting unbounded numbers of steps is impossible, hence we must use different methods. In all our gathering algorithms, changes of the agents' behavior are triggered not by counting steps but by events which are meetings between agents during which they interact. Hence our new technique is event driven. Designing the behavior of the agents based on meeting events, so as to guarantee gathering regardless of the adversary’s decisions is our main methodological contribution.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • Gathering
  • deterministic finite automaton
  • mobile agent
  • team of agents
  • line
  • time

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