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 topology design for network coding deployed large scale sensor networks"):
  Abstract: In this paper, we aim to design a distributed solution to topology formation problem of large- scale sensor networks with multi-source multicast flows. We propose a distributed solution based on game-theoretic approaches in conjunction with network coding. While it is NP-hard to find an optimal topology for network coding deployed multi-source multicast flows, we propose an algorithm that requires significantly low computational complexity. We formulate the problem of distributed network topology formation as a network formation game by considering the nodes in the network as players that can take actions for making outgoing links. We show that the proposed game, which consists of multiple players and multicast flows, can be decomposed into independent link formation games played by only two players with a unicast flow. It is guaranteed that the proposed algorithm is converged, i.e., a stable network topology can be always formed. Our simulation results confirm that the computational complexity of the proposed solution is low enough for practical deployment in large-scale sensor networks.

Includes members:
  Member "network coding based evolutionary network formation for dynamic wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "network coding with random packet index assignment for data collection networks")
  Member "cost efficient qos aware data acquisition point placement for advanced metering infrastructure":
    also connected through other hyperedges:
      (none)
  Member "decoding delay minimization in inter session network coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "network coding based evolutionary network formation for dynamic wireless networks")
  Member "distributed rate allocation in inter session network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "network coding based evolutionary network formation for dynamic wireless networks")
  Member "dynamic network formation with incomplete information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hierarchical network formation games")
  Member "mac centered cooperation synergistic design of network coding multi packet reception and improved fairness to increase network throughput":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "network coding based evolutionary network formation for dynamic wireless networks")
  Member "relay selection with network coding in two way relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy efficient resource allocation for hybrid bursty services in multi relay ofdm networks")
  Member "sensor networks with random links topology design for distributed consensus":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "matcha speeding up decentralized sgd via matching decomposition sampling")

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)