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 "episodic learning with control lyapunov functions for uncertain robotic systems"):
  Abstract: Many modern nonlinear control methods aim to endow systems with guaranteed properties, such as stability or safety, and have been successfully applied to the domain of robotics. However, model uncertainty remains a persistent challenge, weakening theoretical guarantees and causing implementation failures on physical systems. This paper develops a machine learning framework centered around Control Lyapunov Functions (CLFs) to adapt to parametric uncertainty and unmodeled dynamics in general robotic systems. Our proposed method proceeds by iteratively updating estimates of Lyapunov function derivatives and improving controllers, ultimately yielding a stabilizing quadratic program model-based controller. We validate our approach on a planar Segway simulation, demonstrating substantial performance improvements by iteratively refining on a base model-free controller.

Includes members:
  Member "stable gaussian process based tracking control of euler lagrange systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "uniform error bounds for gaussian process regression with application to safe control")
  Member "a control lyapunov perspective on episodic learning via projection to state stability":
    also connected through other hyperedges:
      (none)
  Member "end to end safe reinforcement learning through barrier functions for safety critical continuous control tasks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploration exploitation in constrained mdps")
  Member "neural lander stable drone landing control using learned dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "the lyapunov neural network adaptive stability certification for safe learning of dynamical systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning stable deep dynamics models")
  Member "sim to real learning agile locomotion for quadruped robots":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "a lyapunov based approach to safe reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "constrained upper confidence reinforcement learning")
  Member "accelerating imitation learning with predictive models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "imitation projected programmatic reinforcement learning")

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)