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: "crawford sobel meet lloyd max on the grid"
  Abstract: The main contribution of this work is twofold. First, we apply, for the first time, a framework borrowed from economics to a problem in the smart grid namely, the design of signaling schemes between a consumer and an electricity aggregator when these have non-aligned objectives. The consumer's objective is to meet its need in terms of power and send a request (a message) to the aggregator which does not correspond, in general, to its actual need. The aggregator, which receives this request, not only wants to satisfy it but also wants to manage the cost induced by the residential electricity distribution network. Second, we establish connections between the exploited framework and the quantization problem. Although the model assumed for the payoff functions for the consumer and aggregator is quite simple, it allows one to extract insights of practical interest from the analysis conducted. This allows us to establish a direct connection with quantization, and more importantly, to open a much more general challenge for source and channel coding.

Connected through hyperedge HE-1 (induced by source paper "on the number of bins in equilibria for signaling games"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "estimation with strategic sensors"

Connected through hyperedge HE-2 (induced by source paper "interference coordination via power domain channel estimation"):
  with members:
    - "ultra dense small cell networks turning density into energy efficiency"
    - "coordination in distributed networks via coded actions with application to power control"
    - "resource allocation for energy efficient 3 way relay channels"
    - "compressive rate estimation with applications to device to device communications"
    - "energy aware competitive power allocation for heterogeneous networks under qos constraints"
    - "coded power control performance analysis"
    - "power optimization in random wireless networks"
    - "distributed learning policies for power allocation in multiple access channels"

Connected through hyperedge HE-3 (induced by source paper "game theory for signal processing in networks"):
  with members:
    - "understanding game theory via wireless power control"
    - "coalitional games in miso interference channels epsilon core and coalition structure stable set"
    - "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems"
    - "distributed cooperative sensing in cognitive radio networks an overlapping coalition formation approach"
    - "distributed adaptive networks a graphical evolutionary game theoretic view"
    - "jamming games in the mimo wiretap channel with an active eavesdropper"
    - "distributed learning policies for power allocation in multiple access channels"
    - "on the nash equilibria in decentralized parallel interference channels"

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.OH(Other Computer Science)