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 "human robot collaboration from psychology to social robotics"):
  Abstract: With the advances in robotic technology, research in human-robot collaboration (HRC) has gained in importance. For robots to interact with humans autonomously they need active decision making that takes human partners into account. However, state-of-the-art research in HRC does often assume a leader-follower division, in which one agent leads the interaction. We believe that this is caused by the lack of a reliable representation of the human and the environment to allow autonomous decision making. This problem can be overcome by an embodied approach to HRC which is inspired by psychological studies of human-human interaction (HHI). In this survey, we review neuroscientific and psychological findings of the sensorimotor patterns that govern HHI and view them in a robotics context. Additionally, we study the advances made by the robotic community into the direction of embodied HRC. We focus on the mechanisms that are required for active, physical human-robot collaboration. Finally, we discuss the similarities and differences in the two fields of study which pinpoint directions of future research.

Includes members:
  Member "deep representation learning for human motion prediction and classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "anticipating many futures online human motion prediction and synthesis for human robot collaboration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning human motion models for long term predictions")
  Member "deep predictive policy training using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "let s push things forward a survey on robot pushing")
  Member "self learning and adaptation in a sensorimotor framework":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep predictive policy training using reinforcement learning")
  Member "a sensorimotor reinforcement learning framework for physical human robot interaction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bayesian optimization meets riemannian manifolds in robot learning")
  Member "efficient model learning from joint action demonstrations for human robot collaborative tasks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint goal and strategy inference across heterogeneous demonstrators via reward network distillation")
  Member "end to end training of deep visuomotor policies":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "challenges and countermeasures for adversarial attacks on deep reinforcement learning")
  Member "learning human activities and object affordances from rgb d videos":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic graph convolutional networks")

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)