human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the robotarium a remotely accessible swarm robotics research testbed"
  Abstract: This paper describes the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-robot research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium and discusses the considerations one must take when making complex hardware remotely accessible. In particular, safety must be built into the system already at the design phase without overly constraining what coordinated control programs users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.

Connected through hyperedge HE-1 (induced by source paper "what can robotics research learn from computer vision research"):
  with members:
    - "a mask rcnn baseline for probabilistic object detection"
    - "do imagenet classifiers generalize to imagenet"
    - "the fishyscapes benchmark measuring blind spots in semantic segmentation"
    - "the limits and potentials of deep learning for robotics"
    - "yolov3 an incremental improvement"
    - "towards open world recognition"
    - "orb slam a versatile and accurate monocular slam system"
    - "imagenet large scale visual recognition challenge"

Connected through hyperedge HE-2 (induced by source paper "policy synthesis for factored mdps with graph temporal logic specifications"):
  with members:
    - "graph temporal logic inference for classification and identification"
    - "reward based deception with cognitive bias"
    - "motion and cooperative transportation planning for multi agent systems under temporal logic formulas"
    - "omega regular objectives in model free reinforcement learning"
    - "environment independent task specifications via gltl"
    - "robotic swarm control from spatio temporal specifications"
    - "efficient solution algorithms for factored mdps"

Connected through hyperedge HE-3 (induced by source paper "adaptive task allocation for heterogeneous multi robot teams with evolving and unknown robot capabilities"):
  with members:
    - "control barrier functions theory and applications"
    - "an optimal task allocation strategy for heterogeneous multi robot systems"
    - "self adaptive decision making mechanisms to balance the execution of multiple tasks for a multi robots team"
    - "constraint driven coordinated control of multi robot systems"
    - "analysis of dynamic task allocation in multi robot systems"

Connected through hyperedge HE-4 (induced by source paper "offworld gym open access physical robotics environment for real world reinforcement learning benchmark and research"):
  with members:
    - "replab a reproducible low cost arm benchmark platform for robotic learning"
    - "learning latent state representation for speeding up exploration"
    - "go explore a new approach for hard exploration problems"
    - "pyrep bringing v rep to deep robot learning"
    - "self supervised exploration via disagreement"
    - "provably efficient imitation learning from observation alone"
    - "quasi direct drive for low cost compliant robotic manipulation"
    - "challenges of real world reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "robel robotics benchmarks for learning with low cost robots"):
  with members:
    - "replab a reproducible low cost arm benchmark platform for robotic learning"
    - "active domain randomization"
    - "bayessim adaptive domain randomization via probabilistic inference for robotics simulators"
    - "stochastic latent actor critic deep reinforcement learning with a latent variable model"
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"
    - "deepmind control suite"
    - "learning dexterous in hand manipulation"
    - "dexterous manipulation with deep reinforcement learning efficient general and low cost"

Connected through hyperedge HE-6 (induced by source paper "interactive gibson benchmark for interactive navigation in cluttered environments"):
  with members:
    - "doorgym a scalable door opening environment and baseline agent"
    - "vrkitchen an interactive 3d virtual environment for task oriented learning"
    - "generalization through simulation integrating simulated and real data into deep reinforcement learning for vision based autonomous flight"
    - "deep visual mpc policy learning for navigation"
    - "habitat a platform for embodied ai research"
    - "gibson env real world perception for embodied agents"
    - "unity a general platform for intelligent agents"
    - "on evaluation of embodied navigation agents"

Connected through hyperedge HE-7 (induced by source paper "replab a reproducible low cost arm benchmark platform for robotic learning"):
  with members:
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"
    - "learning dexterous in hand manipulation"
    - "more than a feeling learning to grasp and regrasp using vision and touch"
    - "visual reinforcement learning with imagined goals"
    - "addressing function approximation error in actor critic methods"
    - "robot learning in homes improving generalization and reducing dataset bias"
    - "deep reinforcement learning that matters"
    - "the feeling of success does touch sensing help predict grasp outcomes"

Connected through hyperedge HE-8 (induced by source paper "barrier certified adaptive reinforcement learning with applications to brushbot navigation"):
  with members:
    - "safe learning of quadrotor dynamics using barrier certificates"
    - "constrained policy optimization"
    - "safe multi agent reinforcement learning for autonomous driving"
    - "safe learning of regions of attraction for uncertain nonlinear systems with gaussian processes"
    - "safe policy search for lifelong reinforcement learning with sublinear regret"
    - "adaptive learning in cartesian product of reproducing kernel hilbert spaces"
    - "proximal reinforcement learning a new theory of sequential decision making in primal dual spaces"
    - "practical kernel based reinforcement learning"

Question: Please tell me which class the center node 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)