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 "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.

Includes members:
  Member "robust regression for safe exploration in control":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beyond no regret competitive control via online optimization with memory")
  Member "episodic learning with control lyapunov functions for uncertain robotic systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "beyond no regret competitive control via online optimization with memory")
  Member "sim to multi real transfer of low level robust control policies to multiple quadrotors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning to seek deep reinforcement learning for phototaxis of a nano drone in an obstacle field")
  Member "control regularization for reduced variance reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "glas global to local safe autonomy synthesis for multi robot motion planning with end to end learning")
  Member "neural lander stable drone landing control using learned dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "residual reinforcement learning for robot control":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning contact rich manipulation tasks with rigid position controlled robots learning to force control")
  Member "deep sets":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "stochastic latent residual video prediction")
  Member "learn fast forget slow safe predictive learning control for systems with unknown and changing dynamics performing repetitive tasks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "driving reinforcement learning with models")

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.RO(Robotics)