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 "transfer of tool affordance and manipulation cues with 3d vision data"):
  Abstract: Future service robots working in human environments, such as kitchens, will face situations where they need to improvise. The usual tool for a given task might not be available and the robot will have to use some substitute tool. The robot needs to select an appropriate alternative tool from the candidates available, and also needs to know where to grasp it, how to orient it and what part to use as the end-effector. We present a system which takes as input a candidate tool's point cloud and weight, and outputs a score for how effective that tool is for a task, and how to use it. Our key novelty is in taking a task-driven approach, where the task exerts a top-down influence on how low level vision data is interpreted. This facilitates the type of 'everyday creativity' where an object such as a wine bottle could be used as a rolling pin, because the interpretation of the object is not fixed in advance, but rather results from the interaction between the bottom-up and top-down pressures at run-time. The top-down influence is implemented by transfer: prior knowledge of geometric features that make a tool good for a task is used to seek similar features in a candidate tool. The prior knowledge is learned by simulating Web models performing the tasks. We evaluate on a set of fifty household objects and five tasks. We compare our system with the closest one in the literature and show that we achieve significantly better results

Includes members:
  Member "building machines that learn and think like people":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "deep learning in neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "π nets deep polynomial neural networks")
  Member "end to end training of deep visuomotor policies":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "challenges and countermeasures for adversarial attacks on deep reinforcement learning")
  Member "deep learning for detecting robotic grasps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")
  Member "representation learning a review and new perspectives":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nestedvae isolating common factors via weak supervision")

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)