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: "kick motions for the nao robot using dynamic movement primitives"
  Abstract: In this paper, we present the probably first application of the popular \emph{Dynamic Movement Primitives (DMP)} approach to the domain of soccer-playing humanoid robots. DMPs are known for their ability to imitate previously demonstrated motions as well as to flexibly adapt to unforeseen changes to the desired trajectory with respect to speed and direction. As demonstrated in this paper, this makes them a useful approach for describing kick motions. Furthermore, we present a mathematical motor model that compensates for the NAO robot's motor control delay as well as a novel minor extension to the DMP formulation. The motor model is used in the calculation of the Zero Moment Point (ZMP), which is needed to keep the robot in balance while kicking. All approaches have been evaluated on real NAO robots.

Connected through hyperedge HE-1 (induced by source paper "a survey of behavior learning applications in robotics state of the art and perspectives"):
  with members:
    - "learning dexterous in hand manipulation"
    - "deepmimic example guided deep reinforcement learning of physics based character skills"
    - "deep haptic model predictive control for robot assisted dressing"
    - "one shot visual imitation learning via meta learning"
    - "deep reinforcement learning a brief survey"
    - "learning complex dexterous manipulation with deep reinforcement learning and demonstrations"
    - "combining model based and model free updates for trajectory centric reinforcement learning"
    - "time contrastive networks self supervised learning from video"

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)