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 "reinforcement learning based visual navigation with information theoretic regularization"):
  Abstract: We present a target-driven navigation approach for improving the cross-target and cross-scene generalization for visual navigation. Our approach incorporates an information-theoretic regularization into a deep reinforcement learning (RL) framework. First, we present a supervised generative model to constrain the intermediate process of the RL policy, which is used to generate a future observation from a current observation and a target. Next, we predict a navigation action by analyzing the difference between the generated future and the current. Our approach takes into account the connection between current observations and targets, and the interrelation between actions and visual transformations. This results in a compact and generalizable navigation model. We perform experiments on the AI2-THOR framework and the Active Vision Dataset (AVD) and show at least 7.8% improvement in navigation success rate and 5.7% in SPL, compared to the supervised baseline, in unexplored environments.

Includes members:
  Member "learning a controller fusion network by online trajectory filtering for vision based uav racing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "oil observational imitation learning")
  Member "sim real joint reinforcement transfer for 3d indoor navigation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "manga method agnostic neural policy generalization and adaptation")
  Member "splitnet sim2sim and task2task transfer for embodied visual navigation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "audio visual embodied navigation")
  Member "bayesian relational memory for semantic visual navigation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "from seeing to moving a survey on learning for visual indoor navigation vin")
  Member "reinforcement learning from imperfect demonstrations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploration efficient deep reinforcement learning with demonstration guidance for robot control")
  Member "deep drone racing learning agile flight in dynamic environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to fly via deep model based reinforcement learning")
  Member "a real time game theoretic planner for autonomous two player drone racing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "airsim drone racing lab")
  Member "oil observational imitation learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "safety considerations in deep control policies with probabilistic safety barrier certificates")

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)