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 "active learning of dynamics for data driven control using koopman operators"):
  Abstract: This paper presents an active learning strategy for robotic systems that takes into account task information, enables fast learning, and allows control to be readily synthesized by taking advantage of the Koopman operator representation. We first motivate the use of representing nonlinear systems as linear Koopman operator systems by illustrating the improved model-based control performance with an actuated Van der Pol system. Information-theoretic methods are then applied to the Koopman operator formulation of dynamical systems where we derive a controller for active learning of robot dynamics. The active learning controller is shown to increase the rate of information about the Koopman operator. In addition, our active learning controller can readily incorporate policies built on the Koopman dynamics, enabling the benefits of fast active learning and improved control. Results using a quadcopter illustrate single-execution active learning and stabilization capabilities during free-fall. The results for active learning are extended for automating Koopman observables and we implement our method on real robotic systems.

Includes members:
  Member "learning models for shared control of human machine systems with unknown dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "controlling assistive robots with learned latent actions")
  Member "learning deep neural network representations for koopman operators of nonlinear dynamical systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "decomposition of nonlinear dynamical systems using koopman gramians")
  Member "neural network dynamics for model based deep reinforcement learning with model free fine tuning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "challenges and countermeasures for adversarial attacks on deep reinforcement learning")
  Member "dynamic task execution using active parameter identification with the baxter research robot":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "real time area coverage and target localization using receding horizon ergodic exploration")
  Member "preparing for the unknown learning a universal policy with online system identification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rapidly adaptable legged robots via evolutionary meta learning")
  Member "model based control using koopman operators":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "koopman based control of a soft continuum manipulator under variable loading conditions")
  Member "pulse based control using koopman operator under parametric uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "nonlinear observability via koopman analysis characterizing the role of symmetry")
  Member "sequential action control closed form optimal control for nonlinear and nonsmooth systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "operation and imitation under safety aware shared control")

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)