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 "beyond basins of attraction evaluating robustness of natural dynamics"):
  Abstract: It is commonly accepted that properly designing a system to exhibit favorable natural dynamics can greatly simplify designing or learning the control policy. It is however still unclear what constitutes favorable natural dynamics, and how to quantify its effect. Most studies of simple walking and running models have focused on the basins of attraction of passive limit-cycles, and the notion of self-stability. We emphasize instead the importance of stepping beyond basins of attraction. We show an approach based on viability theory to quantify robustness, valid for the family of all robust control policies. This allows us to evaluate the robustness inherent to the natural dynamics before designing the control policy or specifying a control objective. We illustrate this approach on simple spring mass models of running and show previously unexplored advantages to using a nonlinear leg stiffness. We believe designing robots with robust natural dynamics is partic- ularly important for enabling learning control policies directly in hardware.

Includes members:
  Member "walking with confidence safety regulation for full order biped models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "leveraging the template and anchor framework for safe online robotic gait design")
  Member "gait learning for soft microrobots controlled by light fields":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "classified regression for bayesian optimization robot learning with unknown penalties")
  Member "learning from outside the viability kernel why we should build robots that can fall with grace":
    also connected through other hyperedges:
      (none)
  Member "real time control for autonomous racing based on viability theory":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimization based hierarchical motion planning for autonomous racing")
  Member "robust optimal planning and control of non periodic bipedal locomotion with a centroidal momentum model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nonlinear model predictive control for robust bipedal locomotion exploring com height and angular momentum changes")
  Member "bayesian optimization using domain knowledge on the atrias biped":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning fast adaptation with meta strategy optimization")
  Member "shaping in practice training wheels to learn fast hopping directly in hardware":
    also connected through other hyperedges:
      (none)
  Member "hamilton jacobi reachability a brief overview and recent advances":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an inductive synthesis framework for verifiable 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)