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 game theoretic framework for incentives in p2p systems"
  Abstract: Peer-To-Peer (P2P) networks are self-organizing, distributed systems, with no centralized authority or infrastructure. Because of the voluntary participation, the availability of resources in a P2P system can be highly variable and unpredictable. In this paper, we use ideas from Game Theory to study the interaction of strategic and rational peers, and propose a differential service-based incentive scheme to improve the system's performance.

Connected through hyperedge HE-1 (induced by source paper "computing equilibria in binary networked public goods games"):
  with members:
    - "graphical models for game theory"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-2 (induced by source paper "scalable mobile crowdsensing via peer to peer data sharing"):
  with members:
    - "economic analysis of crowdsourced wireless community networks"
    - "dynamic routing for social information sharing"
    - "an integrated spectrum and information market for green cognitive communications"
    - "providing long term participation incentive in participatory sensing"
    - "a game theoretic analysis of user behaviors in crowdsourced wireless community networks"
    - "mine gold to deliver green cognitive communications"
    - "hysim a hybrid spectrum and information market for tv white space networks"
    - "distributed time sensitive task selection in mobile crowdsensing"

Connected through hyperedge HE-3 (induced by source paper "coalitional graph games for popular content distribution in cognitive radio vanets"):
  with members:
    - "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks"
    - "network formation games among relay stations in next generation wireless networks"
    - "coalitional game theory for communication networks a tutorial"

Connected through hyperedge HE-4 (induced by source paper "long term profit maximizing incentive for crowd sensing in mobile social networks"):
  with members:
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "reputation based incentive protocols in crowdsourcing applications"
    - "exploiting channel memory for joint estimation and scheduling in downlink networks"
    - "perseus randomized point based value iteration for pomdps"

Connected through hyperedge HE-5 (induced by source paper "trust estimation in peer to peer network using blue"):
  with members:
    - "reputation aggregation in peer to peer network using differential gossip algorithm"
    - "trust estimation and aggregation in peer to peer network using differential gossip algorithm"

Connected through hyperedge HE-6 (induced by source paper "trust estimation and aggregation in peer to peer network using differential gossip algorithm"):
  with members:
    - "trust estimation in peer to peer network using blue"

Connected through hyperedge HE-7 (induced by source paper "a game theoretic analysis of incentives in content production and sharing over peer to peer networks"):
  with members:
    - "stackelberg contention games in multiuser networks"

Connected through hyperedge HE-8 (induced by source paper "on resource aware algorithms in epidemic live streaming"):
  with members:
    - "stratification in p2p networks application to bittorrent"
    - "gossiping with multiple messages"

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.GT(Computer Science and Game Theory)