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: "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy"
  Abstract: Game theory has emerged as a novel approach for the coordination of multiagent systems. A fundamental component of this approach is the design of a local utility function for each agent so that their selfish maximization achieves the global objective. In this paper we propose a novel framework to characterize and optimize the worst case performance (price of anarchy) of any resulting equilibrium as a function of the chosen utilities, thus providing a performance certificate for a large class of algorithms. More specifically, we consider a class of resource allocation problems, where each agent selects a subset of the resources with the goal of maximizing a welfare function. First, we show that any smoothness argument is inconclusive for the design problems considered. Motivated by this, we introduce a new approach providing a tight expression for the price of anarchy (PoA) as a function of the chosen utility functions. Leveraging this result, we show how to design the utilities so as to maximize the PoA through a tractable linear program. In Part II we specialize the results to submodular and supermodular welfare functions, discuss complexity issues and provide two applications.

Connected through hyperedge HE-1 (induced by source paper "when smoothness is not enough toward exact quantification and optimization of the price of anarchy"):
  with members:
    - "optimal price of anarchy in cost sharing games"
    - "utility design for distributed resource allocation part i characterizing and optimizing the exact price of anarchy"
    - "the impact of local information on the performance of multiagent systems"
    - "multiagent maximum coverage problems the trade off between anarchy and stability"
    - "learning in games robustness of fast convergence"
    - "the price of anarchy in auctions"
    - "bounding the inefficiency of outcomes in generalized second price auctions"
    - "composable and efficient mechanisms"

Connected through hyperedge HE-2 (induced by source paper "optimal mechanisms for distributed resource allocation"):
  with members:
    - "tight approximation bounds for maximum multi coverage"
    - "optimal price of anarchy in cost sharing games"
    - "intense competition can drive selfish explorers to optimize coverage"
    - "distributed resource allocation through utility design part ii applications to submodular supermodular and set covering problems"
    - "multiagent maximum coverage problems the trade off between anarchy and stability"
    - "learning in games robustness of fast convergence"
    - "a market inspired approach for intersection management in urban road traffic networks"
    - "a unifying tool for bounding the quality of non cooperative solutions in weighted congestion games"

Connected through hyperedge HE-3 (induced by source paper "utilizing information optimally to influence distributed network routing"):
  with members:
    - "the importance of system level information in multiagent systems design cardinality and covering problems"
    - "electric vehicle charging station network equilibrium models and pricing schemes"
    - "informational braess paradox the effect of information on traffic congestion"

Connected through hyperedge HE-4 (induced by source paper "optimal price of anarchy in cost sharing games"):
  with members:
    - "electric vehicle charging station network equilibrium models and pricing schemes"
    - "the impact of local information on the performance of multiagent systems"
    - "spectrum sharing as network congestion games"

Connected through hyperedge HE-5 (induced by source paper "carrots or sticks the effectiveness of subsidies and tolls in congestion games"):
  with members:
    - "utilizing information optimally to influence distributed network routing"

Connected through hyperedge HE-6 (induced by source paper "utility design for distributed resource allocation part ii applications to submodular covering and supermodular problems"):
  with members:
    - "the impact of local information on the performance of multiagent systems"
    - "competitive caching of contents in 5g edge cloud networks"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "stochastic surveillance strategies for spatial quickest detection"
    - "efficient minimization of decomposable submodular functions"
    - "combinatorial auctions with decreasing marginal utilities"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-7 (induced by source paper "distributed resource allocation through utility design part ii applications to submodular supermodular and set covering problems"):
  with members:
    - "multiagent maximum coverage problems the trade off between anarchy and stability"
    - "competitive caching of contents in 5g edge cloud networks"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "stochastic surveillance strategies for spatial quickest detection"
    - "efficient minimization of decomposable submodular functions"
    - "combinatorial auctions with decreasing marginal utilities"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-8 (induced by source paper "multiagent maximum coverage problems the trade off between anarchy and stability"):
  with members:
    - "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"
    - "potential games are necessary to ensure pure nash equilibria in cost sharing games"

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)