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: "design development and experimental realization of a quadrupedal research platform stoch"
  Abstract: In this paper, we present a complete description of the hardware design and control architecture of our custom built quadruped robot, called the `Stoch'. Our goal is to realize a robust, modular, and a reliable quadrupedal platform, using which various locomotion behaviors are explored. This platform enables us to explore different research problems in legged locomotion, which use both traditional and learning based techniques. We discuss the merits and limitations of the platform in terms of exploitation of available behaviours, fast rapid prototyping, reproduction and repair. Towards the end, we will demonstrate trotting, bounding behaviors, and preliminary results in turning. In addition, we will also show various gait transitions i.e., trot-to-turn and trot-to-bound behaviors.

Connected through hyperedge HE-1 (induced by source paper "gait library synthesis for quadruped robots via augmented random search"):
  with members:
    - "hierarchical reinforcement learning for quadruped locomotion"
    - "iterative reinforcement learning based design of dynamic locomotion skills for cassie"
    - "learning agile and dynamic motor skills for legged robots"
    - "policies modulating trajectory generators"
    - "sim to real learning agile locomotion for quadruped robots"
    - "realizing learned quadruped locomotion behaviors through kinematic motion primitives"
    - "learning locomotion skills using deeprl does the choice of action space matter"
    - "proximal policy optimization algorithms"

Connected through hyperedge HE-2 (induced by source paper "learning active spine behaviors for dynamic and efficient locomotion in quadruped robots"):
  with members:
    - "iterative reinforcement learning based design of dynamic locomotion skills for cassie"
    - "sim to real learning agile locomotion for quadruped robots"
    - "oncilla robot a versatile open source quadruped research robot with compliant pantograph legs"
    - "soft actor critic algorithms and applications"
    - "realizing learned quadruped locomotion behaviors through kinematic motion primitives"
    - "proximal policy optimization algorithms"
    - "tensorflow agents efficient batched reinforcement learning in tensorflow"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-3 (induced by source paper "realizing learned quadruped locomotion behaviors through kinematic motion primitives"):
  with members:
    - "sim to real learning agile locomotion for quadruped robots"
    - "feedback control for cassie with deep reinforcement learning"
    - "learning locomotion skills using deeprl does the choice of action space matter"
    - "proximal policy optimization algorithms"
    - "tensorflow agents efficient batched reinforcement learning in tensorflow"
    - "adam a method for stochastic optimization"

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)