human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the parameterized complexity of motion planning for snake like robots"):
  Abstract: We study the parameterized complexity of a variant of the classic video game Snake that models real-world problems of motion planning. Given a snake-like robot with an initial position and a final position in an environment (modeled by a graph), our objective is to determine whether the robot can reach the final position from the initial position without intersecting itself. Naturally, this problem models a wide-variety of scenarios, ranging from the transportation of linked wagons towed by a locomotor at an airport or a supermarket to the movement of a group of agents that travel in an `ant-like' fashion and the construction of trains in amusement parks. Unfortunately, already on grid graphs, this problem is PSPACE-complete [Biasi and Ophelders, 2016]. Nevertheless, we prove that even on general graphs, the problem is solvable in time $k^{\mathcal{O}(k)}|I|^{\mathcal{O}(1)}$ where $k$ is the size of the snake, and $|I|$ is the input size. In particular, this shows that the problem is fixed-parameter tractable (FPT). Towards this, we show how to employ color-coding to sparsify the configuration graph of the problem to have size $k^{\mathcal{O}(k)}|I|^{\mathcal{O}(1)}$ rather than $|I|^{\mathcal{O}(k)}$. We believe that our approach will find other applications in motion planning. Additionally, we show that the problem is unlikely to admit a polynomial kernel even on grid graphs, but it admits a treewidth-reduction procedure. To the best of our knowledge, the study of the parameterized complexity of motion planning problems (where the intermediate configurations of the motion are of importance) has so far been largely overlooked. Thus, our work is pioneering in this regard.

Includes members:
  Member "towards tight er bounds for the excluded grid theorem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards a theory of parameterized streaming algorithms")
  Member "coordinated motion planning reconfiguring a swarm of labeled robots with bounded stretch":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "constant factor time optimal multi robot routing on high dimensional grids in mostly sub quadratic time")
  Member "push pull block puzzles are hard":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a general theory of motion planning complexity characterizing which gadgets make games hard")
  Member "how to navigate through obstacles":
    also connected through other hyperedges:
      (none)
  Member "a survey of motion planning and control techniques for self driving urban vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep reinforcement learning for autonomous driving a survey")
  Member "polynomial bounds for the grid minor theorem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hitting topological minors is fpt")
  Member "kernelization lower bounds by cross composition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")

Question: Please tell me which class the source paper 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)