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 "adding neural network controllers to behavior trees without destroying performance guarantees"):
  Abstract: In this paper, we show how controllers created using data driven designs, such as neural networks, can be used together with model based controllers in a way that combines the performance guarantees of the model based controllers with the efficiency of the data driven controllers. The considered performance guarantees include both safety, in terms of avoiding designated unsafe parts of the state space, and convergence, in terms of reaching a given beneficial part of the state space. Using the framework Behavior Trees, we are able to show how this can be done on the top level, concerning just two controllers, as described above, but also note that the same approach can be used in arbitrary sub-trees. The price for introducing the new controller is that the upper bound on the time needed to reach the desired part of the state space increases. The approach is illustrated with an inverted pendulum example.

Includes members:
  Member "machine learning and evolutionary techniques in interplanetary trajectory design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning a family of optimal state feedback controllers")
  Member "behavior trees in robotics and ai an introduction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "human grasp classification for reactive human to robot handovers")
  Member "a lyapunov based approach to safe reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constrained upper confidence reinforcement learning")
  Member "deep learning for video game playing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improving deep neuroevolution via deep innovation protection")
  Member "simulation results on selector adaptation in behavior trees":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "raven open surgical robotic platforms")
  Member "costar instructing collaborative robots with behavior trees and vision":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "human grasp classification for reactive human to robot handovers")
  Member "learning of behavior trees for autonomous agents":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "integrating acting planning and learning in hierarchical operational models")
  Member "a neural algorithm of artistic style":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deformation aware unpaired image translation for pose estimation on laboratory animals")

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)