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 "distributed learning policies for power allocation in multiple access channels"):
  Abstract: We analyze the problem of distributed power allocation for orthogonal multiple access channels by considering a continuous non-cooperative game whose strategy space represents the users' distribution of transmission power over the network's channels. When the channels are static, we find that this game admits an exact potential function and this allows us to show that it has a unique equilibrium almost surely. Furthermore, using the game's potential property, we derive a modified version of the replicator dynamics of evolutionary game theory which applies to this continuous game, and we show that if the network's users employ a distributed learning scheme based on these dynamics, then they converge to equilibrium exponentially quickly. On the other hand, a major challenge occurs if the channels do not remain static but fluctuate stochastically over time, following a stationary ergodic process. In that case, the associated ergodic game still admits a unique equilibrium, but the learning analysis becomes much more complicated because the replicator dynamics are no longer deterministic. Nonetheless, by employing results from the theory of stochastic approximation, we show that users still converge to the game's unique equilibrium. #R##N#Our analysis hinges on a game-theoretical result which is of independent interest: in finite player games which admit a (possibly nonlinear) convex potential function, the replicator dynamics (suitably modified to account for nonlinear payoffs) converge to an eps-neighborhood of an equilibrium at time of order O(log(1/eps)).

Includes members:
  Member "power allocation games in wireless networks of multi antenna terminals":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coalitional games for transmitter cooperation in mimo multiple access channels")
  Member "dynamic power allocation games in parallel multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cost efficient throughput maximization in multi carrier cognitive radio systems")
  Member "methodologies for analyzing equilibria in wireless games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed multi user wireless charging power allocation")
  Member "on the base station selection and base station sharing in self configuring networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a comprehensive survey of potential game approaches to wireless networks")
  Member "the mimo iterative waterfilling algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed power control with partial channel state information performance characterization and design")
  Member "competitive design of multiuser mimo systems based on game theory a unified view":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "correlated anarchy in overlapping wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the two user multi carrier joint channel selection and power control game")
  Member "optimal linear precoding strategies for wideband non cooperative systems based on game theory part ii algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mixed monotonic programming for fast global optimization")

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)