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În afara temei aiqbench

În afara temei aiqbench

Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.

Asynchronous Indulgent Gathering of Opaque Robots

arXiv3 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2509.10711v2 Announce Type: replace-cross Abstract: We consider the benchmarking problem of gathering in an $(N,f)$-fault system consisting of $N$ robots, of which at most $f$ may fail at any execution. The {\em traditional} version asks $N-f$ non-faulty robots to gather at a point not known a priori. The recently studied {\em indulgent} version asks $N-f$ non-faulty robots to gather at the location of a faulty one. Indulgent gathering is impossible in a $(2,1)$-crash system in the $LUMI$ model under semi-synchrony, even when infinitely many colors and coordinate axis agreement are available. In this paper, we establish four results for indulgent gathering under asynchrony in $LUMI$, considering a {\em mobility fault} model in which a robot crash only impacts its mobility but not the operation of the light. We first show that indulgent gathering is impossible in a $(2,1)$-mobility system using 2-colored lights, and then give an optimal solution w.r.t. the number of colors using 3-colored lights. We then give two deterministic algorithms for an $(N,f)$-mobility system, $f<N$, $N,f$ unknown, that exhibit a nice time-color trade-off: One with time $O(N)$ using 7-colored lights and another with time $O(\max\{\ell,f\})$ using 26-colored lights, where $\ell< N$ is the number of distinct convex layers of robot positions in the initial configuration. Our algorithms for an $(N,f)$-mobility system are the first to be analysed time complexity, can withstand obstructed visibility (opaque robot model) and asynchronous scheduling. Interestingly, our algorithms also solve traditional gathering.

Abstract:We consider the benchmarking problem of gathering in an $(N,f)$-fault system consisting of $N$ robots, of which at most $f$ may fail at any execution. The {\em traditional} version asks $N-f$ non-faulty robots to gather at a point not known a priori. The recently studied {\em indulgent} version asks $N-f$ non-faulty robots to gather at the location of a faulty one. Indulgent gathering is impossible in a $(2,1)$-crash system in the $LUMI$ model under semi-synchrony, even when infinitely many colors and coordinate axis agreement are available. In this paper, we establish four results for indulgent gathering under asynchrony in $LUMI$, considering a {\em mobility fault} model in which a robot crash only impacts its mobility but not the operation of the light. We first show that indulgent gathering is impossible in a $(2,1)$-mobility system using 2-colored lights, and then give an optimal solution w.r.t. the number of colors using 3-colored lights. We then give two deterministic algorithms for an $(N,f)$-mobility system, $f<N$, $N,f$ unknown, that exhibit a nice time-color trade-off: One with time $O(N)$ using 7-colored lights and another with time $O(\max\{\ell,f\})$ using 26-colored lights, where $\ell< N$ is the number of distinct convex layers of robot positions in the initial configuration. Our algorithms for an $(N,f)$-mobility system are the first to be analysed time complexity, can withstand obstructed visibility (opaque robot model) and asynchronous scheduling. Interestingly, our algorithms also solve traditional gathering.

Distributed, Parallel, and Cluster Computing (cs.DC); Multiagent Systems (cs.MA); Robotics (cs.RO)

arXiv:2509.10711 [cs.DC]

(or arXiv:2509.10711v2 [cs.DC] for this version)

https://doi.org/10.48550/arXiv.2509.10711 Focus to learn more arXiv-issued DOI via DataCite

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