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: "reaching a target in the plane with no information"
  Abstract: A mobile agent has to reach a target in the Euclidean plane. Both the agent and the target are modeled as points. In the beginning, the agent is at distance at most $D>0$ from the target. Reaching the target means that the agent gets at a {\em sensing distance} at most $r>0$ from it. The agent has a measure of length and a compass. We consider two scenarios: in the {\em static} scenario the target is inert, and in the {\em dynamic} scenario it may move arbitrarily at any (possibly varying) speed bounded by $v$. The agent has no information about the parameters of the problem, in particular it does not know $D$, $r$ or $v$. The goal is to reach the target at lowest possible cost, measured by the total length of the trajectory of the agent. #R##N#Our main result is establishing the minimum cost (up to multiplicative constants) of reaching the target under both scenarios, and providing the optimal algorithm for the agent. For the static scenario the minimum cost is $\Theta((\log D + \log \frac{1}{r}) D^2/r)$, and for the dynamic scenario it is $\Theta((\log M + \log \frac{1}{r}) M^2/r)$, where $M=\max(D,v)$. Under the latter scenario, the speed of the agent in our algorithm grows exponentially with time, and we prove that for an agent whose speed grows only polynomially with time, this cost is impossible to achieve.

Connected through hyperedge HE-1 (induced by source paper "advice complexity of treasure hunt in geometric terrains"):
  with members:
    - "the graph exploration problem with advice"
    - "impact of knowledge on election time in anonymous networks"
    - "topology recognition with advice"
    - "deterministic graph exploration with advice"
    - "tradeoffs between cost and information for rendezvous and treasure hunt"

Connected through hyperedge HE-2 (induced by source paper "lower bounds for shoreline searching with 2 or more robots"):
  with members:
    - "cost vs information tradeoffs for treasure hunt in the plane"
    - "information complexity of treasure hunt in geometric terrains"
    - "trade offs between selection complexity and performance when searching the plane without communication"

Connected through hyperedge HE-3 (induced by source paper "cost vs information tradeoffs for treasure hunt in the plane"):
  with members:
    - "information complexity of treasure hunt in geometric terrains"
    - "the graph exploration problem with advice"
    - "impact of knowledge on election time in anonymous networks"
    - "topology recognition with advice"
    - "deterministic graph exploration with advice"
    - "time vs information tradeoffs for leader election in anonymous trees"
    - "tradeoffs between cost and information for rendezvous and treasure hunt"

Connected through hyperedge HE-4 (induced by source paper "information complexity of treasure hunt in geometric terrains"):
  with members:
    - "the graph exploration problem with advice"
    - "impact of knowledge on election time in anonymous networks"
    - "topology recognition with advice"
    - "deterministic graph exploration with advice"
    - "time vs information tradeoffs for leader election in anonymous trees"

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)