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: "a general lower bound for collaborative tree exploration"
  Abstract: We consider collaborative graph exploration with a set of $k$ agents. All agents start at a common vertex of an initially unknown graph and need to collectively visit all other vertices. We assume agents are deterministic, vertices are distinguishable, moves are simultaneous, and we allow agents to communicate globally. For this setting, we give the first non-trivial lower bounds that bridge the gap between small ($k \leq \sqrt n$) and large ($k \geq n$) teams of agents. Remarkably, our bounds tightly connect to existing results in both domains. #R##N#First, we significantly extend a lower bound of $\Omega(\log k / \log\log k)$ by Dynia et al. on the competitive ratio of a collaborative tree exploration strategy to the range $k \leq n \log^c n$ for any $c \in \mathbb{N}$. Second, we provide a tight lower bound on the number of agents needed for any competitive exploration algorithm. In particular, we show that any collaborative tree exploration algorithm with $k = Dn^{1+o(1)}$ agents has a competitive ratio of $\omega(1)$, while Dereniowski et al. gave an algorithm with $k = Dn^{1+\varepsilon}$ agents and competitive ratio $O(1)$, for any $\varepsilon > 0$ and with $D$ denoting the diameter of the graph. Lastly, we show that, for any exploration algorithm using $k = n$ agents, there exist trees of arbitrarily large height $D$ that require $\Omega(D^2)$ rounds, and we provide a simple algorithm that matches this bound for all trees.

Connected through hyperedge HE-1 (induced by source paper "improved lower bound for competitive graph exploration"):
  with members:
    - "online graph exploration on a restricted graph class optimal solutions for tadpole graphs"
    - "deterministic graph exploration with advice"

Connected through hyperedge HE-2 (induced by source paper "dispersion of mobile robots in the global communication model"):
  with members:
    - "dispersion of mobile robots the power of randomness"
    - "efficient dispersion of mobile robots on graphs"
    - "efficient dispersion of mobile robots on arbitrary graphs and grids"
    - "dispersion of mobile robots a study of memory time trade offs"
    - "time and space optimality of rotor router graph exploration"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"

Connected through hyperedge HE-3 (induced by source paper "efficient dispersion of mobile robots on graphs"):
  with members:
    - "dispersion of mobile robots a study of memory time trade offs"
    - "deterministic graph exploration with advice"
    - "time and space optimality of rotor router graph exploration"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"

Connected through hyperedge HE-4 (induced by source paper "dispersion of mobile robots a study of memory time trade offs"):
  with members:
    - "efficient dispersion of mobile robots on graphs"
    - "deterministic dispersion of mobile robots in dynamic rings"
    - "on the power of one bit how to explore a graph when you cannot backtrack"
    - "tight bounds for randomized load balancing on arbitrary network topologies"

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.DM(Discrete Mathematics)