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: "neural swarm decentralized close proximity multirotor controlusing learned interactions"
  Abstract: In this paper, we present Neural-Swarm, a nonlinear#R##N#decentralized stable controller for close-proximity flight#R##N#of multirotor swarms. Close-proximity control is challenging#R##N#due to the complex aerodynamic interaction effects between#R##N#multirotors, such as downwash from higher vehicles to lower#R##N#ones. Conventional methods often fail to properly capture these#R##N#interaction effects, resulting in controllers that must maintain#R##N#large safety distances between vehicles, and thus are not capable#R##N#of close-proximity flight. Our approach combines a nominal#R##N#dynamics model with a regularized permutation-invariant Deep#R##N#Neural Network (DNN) that accurately learns the high-order#R##N#multi-vehicle interactions. We design a stable nonlinear tracking#R##N#controller using the learned model. Experimental results demonstrate#R##N#that the proposed controller significantly outperforms a#R##N#baseline nonlinear tracking controller with up to four times#R##N#smaller worst-case height tracking errors. We also empirically#R##N#demonstrate the ability of our learned model to generalize to#R##N#larger swarm sizes.

Connected through hyperedge HE-1 (induced by source paper "beyond no regret competitive control via online optimization with memory"):
  with members:
    - "chasing convex bodies optimally"
    - "robust regression for safe exploration in control"
    - "episodic learning with control lyapunov functions for uncertain robotic systems"
    - "competitive online optimization under inventory constraints"
    - "online control with adversarial disturbances"
    - "beyond online balanced descent an optimal algorithm for smoothed online optimization"
    - "online inventory management with application to energy procurement in data centers"
    - "online optimization with predictions and non convex losses"

Connected through hyperedge HE-2 (induced by source paper "glas global to local safe autonomy synthesis for multi robot motion planning with end to end learning"):
  with members:
    - "trajectory generation for multiagent point to point transitions via distributed model predictive control"
    - "learning safe unlabeled multi robot planning with motion constraints"
    - "control regularization for reduced variance reinforcement learning"
    - "graph neural networks for decentralized multi robot path planning"
    - "graph policy gradients for large scale unlabeled motion planning with constraints"
    - "pytorch an imperative style high performance deep learning library"
    - "differentiable particle filters end to end learning with algorithmic priors"

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)