human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the random bit complexity of mobile robots scattering"
  Abstract: We consider the problem of scattering $n$ robots in a two dimensional continuous space. As this problem is impossible to solve in a deterministic manner, all solutions must be probabilistic. We investigate the amount of randomness (that is, the number of random bits used by the robots) that is required to achieve scattering. We first prove that $n \log n$ random bits are necessary to scatter $n$ robots in any setting. Also, we give a sufficient condition for a scattering algorithm to be random bit optimal. As it turns out that previous solutions for scattering satisfy our condition, they are hence proved random bit optimal for the scattering problem. Then, we investigate the time complexity of scattering when strong multiplicity detection is not available. We prove that such algorithms cannot converge in constant time in the general case and in $o(\log \log n)$ rounds for random bits optimal scattering algorithms. However, we present a family of scattering algorithms that converge as fast as needed without using multiplicity detection. Also, we put forward a specific protocol of this family that is random bit optimal ($n \log n$ random bits are used) and time optimal ($\log \log n$ rounds are used). This improves the time complexity of previous results in the same setting by a $\log n$ factor. Aside from characterizing the random bit complexity of mobile robot scattering, our study also closes its time complexity gap with and without strong multiplicity detection (that is, $O(1)$ time complexity is only achievable when strong multiplicity detection is available, and it is possible to approach it as needed otherwise).

Connected through hyperedge HE-1 (induced by source paper "randomized gathering of asynchronous mobile robots"):
  with members:
    - "optimal rendezvous mathcal l algorithms for asynchronous mobile robots with external lights"
    - "optimally gathering two robots"

Connected through hyperedge HE-2 (induced by source paper "fault induced dynamics of oblivious robots on a line"):
  with members:
    - "come together multi agent geometric consensus gathering rendezvous clustering aggregation"
    - "erratic extremism causes dynamic consensus a new model for one dimensional opinion dynamics"
    - "plane formation by synchronous mobile robots in the three dimensional euclidean space"
    - "distributed computing by mobile robots uniform circle formation"
    - "fault and byzantine tolerant self stabilizing mobile robots gathering feasibility study"
    - "distributed computing by mobile robots solving the uniform circle formation problem"
    - "certified impossibility results for byzantine tolerant mobile robots"
    - "the gathering problem for two oblivious robots with unreliable compasses"

Connected through hyperedge HE-3 (induced by source paper "turingmobile a turing machine of oblivious mobile robots with limited visibility and its applications"):
  with members:
    - "asynchronous pattern formation the effects of a rigorous approach"
    - "plane formation by synchronous mobile robots in the three dimensional euclidean space"
    - "getting close without touching near gathering for autonomous mobile robots"
    - "distributed computing by mobile robots uniform circle formation"
    - "a distributed algorithm for gathering many fat mobile robots in the plane"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DS(Data Structures and Algorithms)