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: "a fleet of miniature cars for experiments in cooperative driving"
  Abstract: We introduce a unique experimental testbed that consists of a fleet of 16 miniature Ackermann-steering vehicles. We are motivated by a lack of available low-cost platforms to support research and education in multi-car navigation and trajectory planning. This article elaborates the design of our miniature robotic car, the Cambridge Minicar, as well as the fleet's control architecture. Our experimental testbed allows us to implement state-of-the-art driver models as well as autonomous control strategies, and test their validity in a real, physical multi-lane setup. Through experiments on our miniature highway, we are able to tangibly demonstrate the benefits of cooperative driving on multi-lane road topographies. Our setup paves the way for indoor large-fleet experimental research.

Connected through hyperedge HE-1 (induced by source paper "multi vehicle mixed reality reinforcement learning for autonomous multi lane driving"):
  with members:
    - "learning safe unlabeled multi robot planning with motion constraints"
    - "sim to multi real transfer of low level robust control policies to multiple quadrotors"
    - "deepracer educational autonomous racing platform for experimentation with sim2real reinforcement learning"
    - "sim to real transfer of robotic control with dynamics randomization"
    - "sim to real learning agile locomotion for quadruped robots"
    - "learning to adapt in dynamic real world environments through meta reinforcement learning"
    - "closing the sim to real loop adapting simulation randomization with real world experience"
    - "addressing function approximation error in actor critic methods"

Connected through hyperedge HE-2 (induced by source paper "multi robot path deconfliction through prioritization by path prospects"):
  with members:
    - "searching with consistent prioritization for multi agent path finding"
    - "job selection in a network of autonomous uavs for delivery of goods"

Connected through hyperedge HE-3 (induced by source paper "demonstration of a time efficient mobility system using a scaled smart city"):
  with members:
    - "on the traffic impacts of optimally controlled connected and automated vehicles"
    - "control of connected and automated vehicles state of the art and future challenges"

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)