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: "an information model for modular robots the hardware robot information model hrim"
  Abstract: Today's landscape of robotics is dominated by vertical integration where single vendors develop the final product leading to slow progress, expensive products and customer lock-in. Opposite to this, an horizontal integration would result in a rapid development of cost-effective mass-market products with an additional consumer empowerment. The transition of an industry from vertical integration to horizontal integration is typically catalysed by de facto industry standards that enable a simplified and seamless integration of products. However, in robotics there is currently no leading candidate for a global plug-and-play standard. #R##N#This paper tackles the problem of incompatibility between robot components that hinder the reconfigurability and flexibility demanded by the robotics industry. Particularly, it presents a model to create plug-and-play robot hardware components. Rather than iteratively evolving previous ontologies, our proposed model answers the needs identified by the industry while facilitating interoperability, measurability and comparability of robotics technology. Our approach differs significantly with the ones presented before as it is hardware-oriented and establishes a clear set of actions towards the integration of this model in real environments and with real manufacturers.

Connected through hyperedge HE-1 (induced by source paper "towards self adaptable robots from programming to training machines"):
  with members:
    - "evaluation of deep reinforcement learning methods for modular robots"
    - "proximal policy optimization algorithms"
    - "extending the openai gym for robotics a toolkit for reinforcement learning using ros and gazebo"

Connected through hyperedge HE-2 (induced by source paper "time synchronization in modular collaborative robots"):
  with members:
    - "time sensitive networking for robotics"

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)