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: "regulating highly automated robot ecologies insights from three user studies"
  Abstract: Highly automated robot ecologies (HARE), or societies of independent autonomous robots or agents, are rapidly becoming an important part of much of the world's critical infrastructure. As with human societies, regulation, wherein a governing body designs rules and processes for the society, plays an important role in ensuring that HARE meet societal objectives. However, to date, a careful study of interactions between a regulator and HARE is lacking. In this paper, we report on three user studies which give insights into how to design systems that allow people, acting as the regulatory authority, to effectively interact with HARE. As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy. Our results show that regulator power, decision support, and adaptive autonomy can each diminish the social welfare of HARE, and hint at how these seemingly desirable mechanisms can be designed so that they become part of successful HARE.

Connected through hyperedge HE-1 (induced by source paper "emerging privacy issues and solutions in cyber enabled sharing services from multiple perspectives"):
  with members:
    - "information design in crowdfunding under thresholding policies"
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"
    - "managing autonomous mobility on demand systems for better passenger experience"
    - "end to end privacy for open big data markets"
    - "the hidden cost of accommodating crowdfunder privacy preferences a randomized field experiment"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "a clustering based location privacy protection scheme for pervasive computing"

Connected through hyperedge HE-2 (induced by source paper "emerging privacy issues and solutions in cyber enabled sharing services from multiple perspectives"):
  with members:
    - "information design in crowdfunding under thresholding policies"
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"
    - "managing autonomous mobility on demand systems for better passenger experience"
    - "end to end privacy for open big data markets"
    - "the hidden cost of accommodating crowdfunder privacy preferences a randomized field experiment"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "a clustering based location privacy protection scheme for pervasive computing"

Connected through hyperedge HE-3 (induced by source paper "toward understanding the impact of user participation in autonomous ridesharing systems"):
  with members:
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"
    - "managing autonomous mobility on demand systems for better passenger experience"

Connected through hyperedge HE-4 (induced by source paper "information design in crowdfunding under thresholding policies"):
  with members:
    - "an online mechanism for ridesharing in autonomous mobility on demand systems"

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.AI(Artificial Intelligence)