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: "finding a needle in an exponential haystack discrete rrt for exploration of implicit roadmaps in multi robot motion planning"
  Abstract: We present a sampling-based framework for multi-robot motion planning which combines an implicit representation of a roadmap with a novel approach for pathfinding in geometrically embedded graphs tailored for our setting. Our pathfinding algorithm, discrete-RRT (dRRT), is an adaptation of the celebrated RRT algorithm for the discrete case of a graph, and it enables a rapid exploration of the high-dimensional configuration space by carefully walking through an implicit representation of a tensor product of roadmaps for the individual robots. We demonstrate our approach experimentally on scenarios of up to 60 degrees of freedom where our algorithm is faster by a factor of at least ten when compared to existing algorithms that we are aware of.

Connected through hyperedge HE-1 (induced by source paper "drrt scalable and informed asymptotically optimal multi robot motion planning"):
  with members:
    - "scalable asymptotically optimal multi robot motion planning"
    - "effective metrics for multi robot motion planning"
    - "batch informed trees bit sampling based optimal planning via the heuristically guided search of implicit random geometric graphs"
    - "motion planning for unlabeled discs with optimality guarantees"
    - "on the hardness of unlabeled multi robot motion planning"
    - "optimal sampling based motion planning under differential constraints the drift case with linear affine dynamics"
    - "efficient multi robot motion planning for unlabeled discs in simple polygons"
    - "k color multi robot motion planning"

Connected through hyperedge HE-2 (induced by source paper "visualizing local minima in multi robot motion planning using morse theory"):
  with members:
    - "multi robot path deconfliction through prioritization by path prospects"
    - "rapidly exploring quotient space trees motion planning using sequential simplifications"
    - "motion planning explorer visualizing local minima using a local minima tree"
    - "path homotopy invariants and their application to optimal trajectory planning"
    - "k color multi robot motion planning"

Connected through hyperedge HE-3 (induced by source paper "asymptotically optimal sampling based planners"):
  with members:
    - "drrt scalable and informed asymptotically optimal multi robot motion planning"
    - "anytime multi arm task and motion planning for pick and place of individual objects via handoffs"
    - "revisiting the asymptotic optimality of rrt"
    - "robot motion planning in learned latent spaces"
    - "probabilistic completeness of rrt for geometric and kinodynamic planning with forward propagation"
    - "fast anytime motion planning for prehensile manipulation in clutter"
    - "group marching tree sampling based approximately optimal motion planning on gpus"
    - "the provable virtue of laziness in motion planning"

Connected through hyperedge HE-4 (induced by source paper "anytime multi arm task and motion planning for pick and place of individual objects via handoffs"):
  with members:
    - "drrt scalable and informed asymptotically optimal multi robot motion planning"
    - "towards robust product packing with a minimalistic end effector"
    - "admissible abstractions for near optimal task and motion planning"
    - "fast high quality dual arm rearrangement in synchronous monotone tabletop setups"
    - "ffrob leveraging symbolic planning for efficient task and motion planning"
    - "scalable asymptotically optimal multi robot motion planning"
    - "analysis and observations from the first amazon picking challenge"
    - "on the power of manifold samples in exploring configuration spaces and the dimensionality of narrow passages"

Connected through hyperedge HE-5 (induced by source paper "object rearrangement with nested nonprehensile manipulation actions"):
  with members:
    - "towards robust product packing with a minimalistic end effector"
    - "inferring 3d shapes of unknown rigid objects in clutter through inverse physics reasoning"
    - "sample efficient learning of nonprehensile manipulation policies via physics based informed state distributions"
    - "sampling based methods for factored task and motion planning"
    - "automated motion planning for robotic assembly of discrete architectural structures"
    - "ffrob leveraging symbolic planning for efficient task and motion planning"
    - "rearrangement with nonprehensile manipulation using deep reinforcement learning"
    - "efficient high quality stack rearrangement"

Connected through hyperedge HE-6 (induced by source paper "towards scalable continuous time trajectory optimization for multi robot navigation"):
  with members:
    - "trajectory generation for multiagent point to point transitions via distributed model predictive control"
    - "online trajectory generation with distributed model predictive control for multi robot motion planning"
    - "safe aggressive quadrotor flight via reachability based trajectory design"
    - "continuous time trajectory optimization for decentralized multi robot navigation"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"
    - "linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles"
    - "an effective algorithmic framework for near optimal multi robot path planning"

Connected through hyperedge HE-7 (induced by source paper "tethered tool manipulation planning with cable maneuvering"):
  with members:
    - "reinforcement learning in topology based representation for human body movement with whole arm manipulation"
    - "arm manipulation planning of tethered tools with the help of a tool balancer"
    - "learning sampling distributions for robot motion planning"
    - "manipulation planning under changing external forces"
    - "deep visual foresight for planning robot motion"
    - "developing and comparing single arm and dual arm regrasp"
    - "backward forward search for manipulation planning"

Connected through hyperedge HE-8 (induced by source paper "continuous time trajectory optimization for decentralized multi robot navigation"):
  with members:
    - "high speed trajectory planning for autonomous vehicles using a simple dynamic model"
    - "real time trajectory replanning for mavs using uniform b splines and a 3d circular buffer"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"

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.RO(Robotics)