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 "on the learning behavior of adaptive networks part i transient analysis"):
  Abstract: This work carries out a detailed transient analysis of the learning behavior of multi-agent networks, and reveals interesting results about the learning abilities of distributed strategies. Among other results, the analysis reveals how combination policies influence the learning process of networked agents, and how these policies can steer the convergence point towards any of many possible Pareto optimal solutions. The results also establish that the learning process of an adaptive network undergoes three (rather than two) well-defined stages of evolution with distinctive convergence rates during the first two stages, while attaining a finite mean-square-error (MSE) level in the last stage. The analysis reveals what aspects of the network topology influence performance directly and suggests design procedures that can optimize performance by adjusting the relevant topology parameters. Interestingly, it is further shown that, in the adaptation regime, each agent in a sparsely connected network is able to achieve the same performance level as that of a centralized stochastic-gradient strategy even for left-stochastic combination strategies. These results lead to a deeper understanding and useful insights on the convergence behavior of coupled distributed learners. The results also lead to effective design mechanisms to help diffuse information more thoroughly over networks.

Includes members:
  Member "dictionary learning over distributed models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "supervised learning under distributed features")
  Member "distributed policy evaluation under multiple behavior strategies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "provably convergent two timescale off policy actor critic with function approximation")
  Member "analysis of sum weight like algorithms for averaging in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sample greedy gossip distributed kalman filter")
  Member "distributed pareto optimization via diffusion strategies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "supervised learning under distributed features")
  Member "on the learning behavior of adaptive networks part ii performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "inverse graph learning over optimization networks")
  Member "diffusion adaptation over networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparsity constrained distributed unmixing of hyperspectral data")
  Member "performance limits for distributed estimation over lms adaptive networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "detection under one bit messaging over adaptive networks")
  Member "convergence rate analysis of distributed gossip linear parameter estimation fundamental limits and tradeoffs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "supervised learning under distributed features")

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.MA(Multiagent Systems)