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 cooperative spectrum sharing in uav networks using multi agent reinforcement learning"):
  Abstract: In this paper, we develop a distributed mechanism for spectrum sharing among a network of unmanned aerial vehicles (UAV) and licensed terrestrial networks. This method can provide a practical solution for situations where the UAV network may need external spectrum when dealing with congested spectrum or need to change its operating frequency due to security threats. Here we study a scenario where the UAV network performs a remote sensing mission. In this model, the UAVs are categorized into two clusters of relaying and sensing UAVs. The relay UAVs provide a relaying service for a licensed network to obtain spectrum access for the rest of UAVs that perform the sensing task. We develop a distributed mechanism in which the UAVs locally decide whether they need to participate in relaying or sensing considering the fact that communications among UAVs may not be feasible or reliable. The UAVs learn the optimal task allocation using a distributed reinforcement learning algorithm. Convergence of the algorithm is discussed and simulation results are presented for different scenarios to verify the convergence.

Includes members:
  Member "a reputation based stackelberg game model to enhance secrecy rate in spectrum leasing to selfish iot devices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on hardware based security mechanisms for internet of things")
  Member "leader follower based coalition formation in large scale uav networks a quantum evolutionary approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wildfire monitoring in remote areas using autonomous unmanned aerial vehicles")
  Member "on greedy routing in dynamic uav networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wildfire monitoring in remote areas using autonomous unmanned aerial vehicles")
  Member "a unified framework for joint mobility prediction and object profiling of drones in uav networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wildfire monitoring in remote areas using autonomous unmanned aerial vehicles")
  Member "optimal measurement policy for predicting uav network topology":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wildfire monitoring in remote areas using autonomous unmanned aerial vehicles")
  Member "a coalition formation approach to coordinated task allocation in heterogeneous uav networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wildfire monitoring in remote areas using autonomous unmanned aerial vehicles")
  Member "deep reinforcement learning an overview":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey of optimization methods from a machine learning perspective")
  Member "optimal transport theory for power efficient deployment of unmanned aerial vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "heuristic approach for jointly optimizing feicic and uav locations in multi tier lte advanced public safety hetnet")

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)