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 "gait library synthesis for quadruped robots via augmented random search"):
  Abstract: In this paper, with a view toward fast deployment of learned locomotion gaits in low-cost hardware, we generate a library of walking trajectories, namely, forward trot, backward trot, side-step, and turn in our custom-built quadruped robot, Stoch 2, using reinforcement learning. There are existing approaches that determine optimal policies for each time step, whereas we determine an optimal policy, in the form of end-foot trajectories, for each half walking step i.e., swing phase and stance phase. The way-points for the foot trajectories are obtained from a linear policy, i.e., a linear function of the states of the robot, and cubic splines are used to interpolate between these points. Augmented Random Search, a model-free and gradient-free learning algorithm is used to learn the policy in simulation. This learned policy is then deployed on hardware, yielding a trajectory in every half walking step. Different locomotion patterns are learned in simulation by enforcing a preconfigured phase shift between the trajectories of different legs. The transition from one gait to another is achieved by using a low-pass filter for the phase, and the sim-to-real transfer is improved by a linear transformation of the states obtained through regression.

Includes members:
  Member "hierarchical reinforcement learning for quadruped locomotion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gym ignition reproducible robotic simulations for reinforcement learning")
  Member "iterative reinforcement learning based design of dynamic locomotion skills for cassie":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to manipulate object collections using grounded state representations")
  Member "design development and experimental realization of a quadrupedal research platform stoch":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning active spine behaviors for dynamic and efficient locomotion in quadruped robots")
  Member "learning agile and dynamic motor skills for legged robots":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "rapidly adaptable legged robots via evolutionary meta learning")
  Member "policies modulating trajectory generators":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multiplicative controller fusion a hybrid navigation strategy for deployment in unknown environments")
  Member "sim to real learning agile locomotion for quadruped robots":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "realizing learned quadruped locomotion behaviors through kinematic motion primitives":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "rapidly adaptable legged robots via evolutionary meta learning")
  Member "learning locomotion skills using deeprl does the choice of action space matter":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "q learning in enormous action spaces via amortized approximate maximization")

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)