human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "computation offloading and activation of mobile edge computing servers a minority game"
  Abstract: With the ever-increasing popularity of resource-intensive mobile applications, Mobile Edge Computing (MEC), e.g., offloading computationally expensive tasks to the cellular edge, has become a prominent technology for the next generation wireless networks. Despite its great performance in terms of delay and energy, MEC suffers from restricted power allowance and computational capability of the edge nodes. Therefore, it is imperative to develop distributed mechanisms for computation offloading, so that not only the computational servers are utilized at their best capacity, but also the users' latency constraints are fulfilled. In this paper, by using the theory of Minority Games, we develop a novel distributed server activation mechanism for computational offloading. Our scheme guarantees energy-efficient activation of servers as well as satisfaction of users' quality-of-experience (QoE) requirements in terms of latency.

Connected through hyperedge HE-1 (induced by source paper "an efficient mechanism for computation offloading in mobile edge computing"):
  with members:
    - "price based resource allocation for edge computing a market equilibrium approach"
    - "non cooperative game approach for task offloading in edge clouds"
    - "latency optimization for resource allocation in mobile edge computation offloading"
    - "price based distributed offloading for mobile edge computing with computation capacity constraints"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "efficient multi user computation offloading for mobile edge cloud computing"

Connected through hyperedge HE-2 (induced by source paper "multi armed bandit for energy efficient and delay sensitive edge computing in dynamic networks with uncertainty"):
  with members:
    - "multi armed bandits with application to 5g small cells"
    - "thompson sampling for budgeted multi armed bandits"
    - "optimization of radio and computational resources for energy efficiency in latency constrained application offloading"
    - "knapsack based optimal policies for budget limited multi armed bandits"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Question: Please tell me which class the center node 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)