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 "learning how to walk warm starting optimal control solver with memory of motion"):
  Abstract: In this paper, we propose a framework to build a memory of motion to warm-start an optimal control solver for the locomotion task of the humanoid robot Talos. We use HPP Loco3D, a versatile locomotion planner, to generate offline a set of dynamically consistent whole-body trajectory to be stored as the memory of motion. The learning problem is formulated as a regression problem to predict a single-step motion given the desired contact locations, which is then used as building block for multi-step motions. The predicted trajectory is then used as warm-starts for the fast optimal control solver Crocoddyl. We have shown that the approach manages to reduce the required number of iterations to reach the convergence from $\sim$9.5 to only $\sim$3.0 iterations for the single-step motion and from $\sim$6.2 to $\sim$4.5 iterations for the multi-step motion, while maintaining the solution's quality.

Includes members:
  Member "memory of motion for warm starting trajectory optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a memory of motion for visual predictive control tasks")
  Member "crocoddyl an efficient and versatile framework for multi contact optimal control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimizing dynamic trajectories for robustness to disturbances using polytopic projections")
  Member "passive whole body control for quadruped robots experimental validation over challenging terrain":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stance locomotion adaptation over soft terrain")
  Member "differential dynamic programming for multi phase rigid contact dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "accelerated admm based trajectory optimization for legged locomotion with coupled rigid body dynamics")
  Member "simultaneous contact gait and motion planning for robust multi legged locomotion via mixed integer convex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "whole body walking generation using contact parametrization a non linear trajectory optimization approach")
  Member "trajectory optimization through contacts and automatic gait discovery for quadrupeds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning agile and dynamic motor skills for legged robots")
  Member "planning and execution of dynamic whole body locomotion for a hydraulic quadruped on challenging terrain":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "heuristic planning for rough terrain locomotion in presence of external disturbances and variable perception quality")

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)