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 "self supervised damage avoiding manipulation strategy optimization via mental simulation"):
  Abstract: Everyday robotics are challenged to deal with autonomous product handling in applications like logistics or retail, possibly causing damage on the items during manipulation. Traditionally, most approaches try to minimize physical interaction with goods. However, this paper proposes to take into account any unintended object motion and to learn damage-minimizing manipulation strategies in a self-supervised way. The presented approach consists of a simulation-based planning method for an optimal manipulation sequence with respect to possible damage. The planned manipulation sequences are generalized to new, unseen scenes in the same application scenario using machine learning. This learned manipulation strategy is continuously refined in a self-supervised, simulation-in-the-loop optimization cycle during load-free times of the system, commonly known as mental simulation. In parallel, the generated manipulation strategies can be deployed in near-real time in an anytime fashion. The approach is validated on an industrial container-unloading scenario and on a retail shelf-replenishment scenario.

Includes members:
  Member "kittingbot a mobile manipulation robot for collaborative kitting in automotive logistics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards mobile multi task manipulation in a confined and integrated environment with irregular objects")
  Member "physics based damage aware manipulation strategy planning using scene dynamics anticipation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "self supervised damage avoiding manipulation strategy optimization via mental simulation")
  Member "knowledge enabled robotic agents for shelf replenishment in cluttered retail environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "manipulation planning and control for shelf replenishment")
  Member "learning hand eye coordination for robotic grasping with deep learning and large scale data collection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "scaling data driven robotics with reward sketching and batch reinforcement learning")
  Member "analysis and observations from the first amazon picking challenge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust 6d object pose estimation by learning rgb d features")
  Member "what happens if learning to predict the effect of forces in images":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "belief regulated dual propagation nets for learning action effects on groups of articulated objects")
  Member "robotic playing for hierarchical complex skill learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how a minimal learning agent can infer the existence of unobserved variables in a complex environment")

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)