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: "nash social welfare approximation for strategic agents"
  Abstract: The fair division of resources is an important age-old problem that has led to a rich body of literature. At the center of this literature lies the question of whether there exist fair mechanisms despite strategic behavior of the agents. A fundamental objective function used for measuring fair outcomes is the Nash social welfare, defined as the geometric mean of the agent utilities. This objective function is maximized by widely known solution concepts such as Nash bargaining and the competitive equilibrium with equal incomes. In this work we focus on the question of (approximately) implementing the Nash social welfare. The starting point of our analysis is the Fisher market, a fundamental model of an economy, whose benchmark is precisely the (weighted) Nash social welfare. We begin by studying two extreme classes of valuations functions, namely perfect substitutes and perfect complements, and find that for perfect substitutes, the Fisher market mechanism has a constant approximation: at most 2 and at least e1e. However, for perfect complements, the Fisher market does not work well, its bound degrading linearly with the number of players. #R##N#Strikingly, the Trading Post mechanism---an indirect market mechanism also known as the Shapley-Shubik game---has significantly better performance than the Fisher market on its own benchmark. Not only does Trading Post achieve an approximation of 2 for perfect substitutes, but this bound holds for all concave utilities and becomes arbitrarily close to optimal for Leontief utilities (perfect complements), where it reaches $(1+\epsilon)$ for every $\epsilon > 0$. Moreover, all the Nash equilibria of the Trading Post mechanism are pure for all concave utilities and satisfy an important notion of fairness known as proportionality.

Connected through hyperedge HE-1 (induced by source paper "fair by design matching"):
  with members:
    - "fairness behind a veil of ignorance a welfare analysis for automated decision making"
    - "balancing lexicographic fairness and a utilitarian objective with application to kidney exchange"
    - "algorithmic decision making and the cost of fairness"
    - "fairness in learning classic and contextual bandits"
    - "fairness through awareness"
    - "perfect matchings in o n 1 5 time in regular bipartite graphs"

Connected through hyperedge HE-2 (induced by source paper "monotonicity and competitive equilibrium in cake cutting"):
  with members:
    - "competitive division of a mixed manna"
    - "resource monotonicity and population monotonicity in connected cake cutting"
    - "continuity assumptions in cake cutting"
    - "redividing the cake"
    - "an algorithmic framework for strategic fair division"
    - "cake cutting algorithms for piecewise constant and piecewise uniform valuations"
    - "online cake cutting"

Connected through hyperedge HE-3 (induced by source paper "tit for tat dynamics and market volatility"):
  with members:
    - "proportional dynamics in exchange economies"
    - "universal growth in production economies"
    - "dynamics of distributed updating in fisher markets"
    - "a price anticipating resource allocation mechanism for distributed shared clusters"

Connected through hyperedge HE-4 (induced by source paper "optimal nash equilibria for bandwidth allocation"):
  with members:
    - "markets for public decision making"
    - "markets beyond nash welfare for leontief utilities"
    - "nash equilibria in fisher market"

Connected through hyperedge HE-5 (induced by source paper "a truthful cardinal mechanism for one sided matching"):
  with members:
    - "social welfare in one sided matching mechanisms"
    - "social welfare in one sided matchings random priority and beyond"
    - "the complexity of fairness through equilibrium"

Connected through hyperedge HE-6 (induced by source paper "universal growth in production economies"):
  with members:
    - "selling complementary goods dynamics efficiency and revenue"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "the price of anarchy in auctions"
    - "learning and efficiency in games with dynamic population"
    - "learning in auctions regret is hard envy is easy"
    - "average case performance of replicator dynamics in potential games via computing regions of attraction"
    - "concave generalized flows with applications to market equilibria"
    - "non price equilibria in markets of discrete goods"

Connected through hyperedge HE-7 (induced by source paper "a market based framework for multi resource allocation in fog computing"):
  with members:
    - "price based resource allocation for edge computing a market equilibrium approach"
    - "a survey on mobile edge computing the communication perspective"
    - "the complexity of non monotone markets"
    - "fair allocation without trade"
    - "nash equilibria in fisher market"

Connected through hyperedge HE-8 (induced by source paper "fair by design algorithms matching problems and beyond"):
  with members:
    - "fairness through awareness"

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)