human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "game of thrones fully distributed learning for multi player bandits"):
  Abstract: We consider a multi-armed bandit game where N players compete for M arms for T turns. Each player has different expected rewards for the arms, and the instantaneous rewards are independent and identically distributed or Markovian. When two or more players choose the same arm, they all receive zero reward. Performance is measured using the expected sum of regrets, compared to optimal assignment of arms to players. We assume that each player only knows her actions and the reward she received each turn. Players cannot observe the actions of other players, and no communication between players is possible. We present a distributed algorithm and prove that it achieves an expected sum of regrets of near-O\left(\log T\right). This is the first algorithm to achieve a near order optimal regret in this fully distributed scenario. All other works have assumed that either all players have the same vector of expected rewards or that communication between players is possible.

Includes members:
  Member "distributed learning for channel allocation over a shared spectrum":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning for resource management in cellular and iot networks potentials current solutions and open challenges")
  Member "coordinated exploration in concurrent reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "population guided parallel policy search for reinforcement learning")
  Member "mnl bandit a dynamic learning approach to assortment selection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "combinatorial bandits with relative feedback")
  Member "the effect of communication on noncooperative multiplayer multi armed bandit problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "my fair bandit distributed learning of max min fairness with multi player bandits")
  Member "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the gossiping insert eliminate algorithm for multi agent bandits")
  Member "distributed clustering of linear bandits in peer to peer networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "regret bounds for decentralized learning in cooperative multi agent dynamical systems")
  Member "delay and cooperation in nonstochastic bandits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the gossiping insert eliminate algorithm for multi agent bandits")
  Member "multi user lax communications a multi armed bandit approach":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the gossiping insert eliminate algorithm for multi agent bandits")

Question: Please tell me which class the source paper 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)