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 "results from the robocademy itn autonomy disturbance rejection and perception for advanced marine robotics"):
  Abstract: Marine and Underwater resources are important part of the economy of many countries. This requires significant financial resources into their construction and maintentance. Robotics is expected to fill this void, by automating and/or removing humans from hostile environments in order to easily perform maintenance tasks. The Robocademy Marie Sklodowska-Curie Initial Training Network was funded by the European Union's FP7 research program in order to train 13 Fellows into world-leading researchers in Marine and Underwater Robotics. The fellows developed guided research into three areas of key importance: Autonomy, Disturbance Rejection, and Perception. This paper presents a summary of the fellows' research in the three action lines. 71 scientific publications were the primary result of this project, with many other publications currently in the pipeline. Most of the fellows have found employment in Europe, which shows the high demand for this kind of experts. We believe the results from this project are already having an impact in the marine robotics industry, as key technologies are being adopted already.

Includes members:
  Member "robust trajectory tracking control for underactuated autonomous underwater vehicles":
    also connected through other hyperedges:
      (none)
  Member "decentralized impedance control for cooperative manipulation of multiple underwater vehicle manipulator systems under lean communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust trajectory tracking control for underactuated autonomous underwater vehicles")
  Member "a distributed predictive control approach for cooperative manipulation of multiple underwater vehicle manipulator systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust trajectory tracking control for underactuated autonomous underwater vehicles")
  Member "improving sonar image patch matching via deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "conet a cognitive ocean network")
  Member "decentralized abstractions and timed constrained planning of a general class of coupled multi agent systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a distributed predictive control approach for cooperative manipulation of multiple underwater vehicle manipulator systems")
  Member "a nonlinear model predictive control scheme for cooperative manipulation with singularity and collision avoidance":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a distributed predictive control approach for cooperative manipulation of multiple underwater vehicle manipulator systems")
  Member "a robust model predictive control approach for autonomous underwater vehicles operating in a constrained workspace":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust trajectory tracking control for underactuated autonomous underwater vehicles")
  Member "squeezenet alexnet level accuracy with 50x fewer parameters and 0 5mb model size":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "lossless compression of deep neural 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)