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: "potential games are necessary to ensure pure nash equilibria in cost sharing games"
  Abstract: We consider the problem of designing distribution rules to share "welfare" (cost or revenue) among individually strategic agents. There are many known distribution rules that guarantee the existence of a (pure) Nash equilibrium in this setting, e.g., the Shapley value and its weighted variants; however, a characterization of the space of distribution rules that guarantee the existence of a Nash equilibrium is unknown. Our work provides an exact characterization of this space for a specific class of scalable and separable games, which includes a variety of applications such as facility location, routing, network formation, and coverage games. Given arbitrary local welfare functions W, we prove that a distribution rule guarantees equilibrium existence for all games (i.e., all possible sets of resources, agent action sets, etc.) if and only if it is equivalent to a generalized weighted Shapley value on some "ground" welfare functions W', which can be distinct from W. However, if budget-balance is required in addition to the existence of a Nash equilibrium, then W' must be the same as W. We also provide an alternate characterization of this space in terms of "generalized" marginal contributions, which is more appealing from the point of view of computational tractability. A possibly surprising consequence of our result is that, in order to guarantee equilibrium existence in all games with any fixed local welfare functions, it is necessary to work within the class of potential games.

Connected through hyperedge HE-1 (induced by source paper "cost sharing games for energy efficient multi hop broadcast in wireless networks"):
  with members:
    - "joint caching and pricing strategies for popular content in information centric networks"
    - "decentralised learning macs for collision free access in wlans"

Connected through hyperedge HE-2 (induced by source paper "value of information in bayesian routing games"):
  with members:
    - "informational braess paradox the effect of information on traffic congestion"

Connected through hyperedge HE-3 (induced by source paper "can taxes improve congestion on all networks"):
  with members:
    - "path deviations outperform approximate stability in heterogeneous congestion games"
    - "asymptotically tight bounds for inefficiency in risk averse selfish routing"
    - "achieving target equilibria in network routing games without knowing the latency functions"
    - "playing the wrong game smoothness bounds for congestion games with behavioral biases"

Connected through hyperedge HE-4 (induced by source paper "on the price of anarchy of cost sharing in real time scheduling systems"):
  with members:
    - "sharing non anonymous costs of multiple resources optimally"
    - "a model for minimizing active processor time"
    - "efficient coordination mechanisms for unrelated machine scheduling"

Connected through hyperedge HE-5 (induced by source paper "a characterization of undirected graphs admitting optimal cost shares"):
  with members:
    - "inefficiencies in network models a graph theoretic perspective"
    - "designing networks with good equilibria under uncertainty"
    - "an h n 2 upper bound on the price of stability of undirected network design games"
    - "sharing non anonymous costs of multiple resources optimally"
    - "resource buying games"
    - "an o lognloglogn upper bound on the price of stability for undirected shapley network design games"

Connected through hyperedge HE-6 (induced by source paper "computing approximate pure nash equilibria in shapley value weighted congestion games"):
  with members:
    - "sharing non anonymous costs of multiple resources optimally"
    - "shapley meets shapley"
    - "efficient computation of approximate pure nash equilibria in congestion games"
    - "approximate pure nash equilibria in weighted congestion games existence efficient computation and structure"

Connected through hyperedge HE-7 (induced by source paper "multiagent maximum coverage problems the trade off between anarchy and stability"):
  with members:
    - "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy"
    - "the pareto frontier of inefficiency in mechanism design"
    - "utility design for distributed resource allocation part ii applications to submodular covering and supermodular problems"
    - "distributed resource allocation through utility design part ii applications to submodular supermodular and set covering problems"

Connected through hyperedge HE-8 (induced by source paper "are multiagent systems resilient to communication failures"):
  with members:
    - "fast convergence in semi anonymous potential games"
    - "dynamics in near potential games"
    - "using collective intelligence to route internet traffic"

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)