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 "active reward learning for co robotic vision based exploration in bandwidth limited environments"):
  Abstract: We present a novel POMDP problem formulation for a robot that must autonomously decide where to go to collect new and scientifically relevant images given a limited ability to communicate with its human operator. From this formulation we derive constraints and design principles for the observation model, reward model, and communication strategy of such a robot, exploring techniques to deal with the very high-dimensional observation space and scarcity of relevant training data. We introduce a novel active reward learning strategy based on making queries to help the robot minimize path "regret" online, and evaluate it for suitability in autonomous visual exploration through simulations. We demonstrate that, in some bandwidth-limited environments, this novel regret-based criterion enables the robotic explorer to collect up to 17% more reward per mission than the next-best criterion.

Includes members:
  Member "information guided robotic maximum seek and sample in partially observable continuous environments":
    also connected through other hyperedges:
      (none)
  Member "streaming scene maps for co robotic exploration in bandwidth limited environments":
    also connected through other hyperedges:
      (none)
  Member "the unreasonable effectiveness of deep features as a perceptual metric":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "an approach to autonomous science by modeling geological knowledge in a bayesian framework":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a versatile multi robot monte carlo tree search planner for on line coverage path planning")
  Member "feature discovery and visualization of robot mission data using convolutional autoencoders and bayesian nonparametric topic models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tackling climate change with machine learning")
  Member "modeling curiosity in a mobile robot for long term autonomous exploration and monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "persistification of robotic tasks")
  Member "unsupervised deep feature extraction for remote sensing image classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving the detection of burnt areas in remote sensing using hyper features evolved by m3gp")
  Member "anomaly detection in unstructured environments using bayesian nonparametric scene modeling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "streaming scene maps for co robotic exploration in bandwidth limited environments")

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)