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 "rl based user association and resource allocation for multi uav enabled mec"):
  Abstract: In this paper, multi-unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC), i.e., UAVE is studied, where several UAVs are deployed as flying MEC platform to provide computing resource to ground user equipments (UEs). Compared to the traditional fixed location MEC, UAV enabled MEC (i.e., UAVE) is particular useful in case of temporary events, emergency situations and on-demand services, due to its high flexibility, low cost and easy deployment features. However, operation of UAVE faces several challenges, two of which are how to achieve both 1) the association between multiple UEs and UAVs and 2) the resource allocation from UAVs to UEs, while minimizing the energy consumption for all the UEs. To address this, we formulate the above problem into a mixed integer nonlinear programming (MINLP), which is difficult to be solved in general, especially in the large-scale scenario. We then propose a Reinforcement Learning (RL)-based user Association and resource Allocation (RLAA) algorithm to tackle this problem efficiently and effectively. Numerical results show that the proposed RLAA can achieve the optimal performance with comparison to the exhaustive search in small scale, and have considerable performance gain over other typical algorithms in large-scale cases.

Includes members:
  Member "placement optimization of uav mounted mobile base stations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "optimal task allocation in near far computing enhanced c ran for wireless big data processing":
    also connected through other hyperedges:
      (none)
  Member "joint altitude and beamwidth optimization for uav enabled multiuser communications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient resource allocation in uav enabled mobile edge computing networks")
  Member "decentralized computation offloading game for mobile cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "context aware distribution of fog applications using deep reinforcement learning")

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.NI(Networking and Internet Architecture)