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: "dynamics of distributed updating in fisher markets"
  Abstract: A major goal in Algorithmic Game Theory is to justify equilibrium concepts from an algorithmic and complexity perspective. One appealing approach is to identify natural distributed algorithms that converge quickly to an equilibrium. This paper established new convergence results for two generalizations of Proportional Response in Fisher markets with buyers having CES utility functions. The starting points are respectively a new convex and a new convex-concave formulation of such markets. The two generalizations correspond to suitable mirror descent algorithms applied to these formulations. Several of our new results are a consequence of new notions of strong Bregman convexity and of strong Bregman convex-concave functions, and associated linear rates of convergence, which may be of independent interest. #R##N#Among other results, we analyze a damped generalized Proportional Response and show a linear rate of convergence in a Fisher market with buyers whose utility functions cover the full spectrum of CES utilities aside the extremes of linear and Leontief utilities; when these utilities are included, we obtain an empirical O(1/T) rate of convergence.

Connected through hyperedge HE-1 (induced by source paper "proportional dynamics in exchange economies"):
  with members:
    - "an alternating algorithm for finding linear arrow debreu market equilibrium"
    - "universal growth in production economies"
    - "a strongly polynomial algorithm for linear exchange markets"
    - "tracing equilibrium in dynamic markets via distributed adaptation"
    - "selling complementary goods dynamics efficiency and revenue"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "the price of anarchy in auctions"
    - "ascending price algorithms for unknown markets"

Connected through hyperedge HE-2 (induced by source paper "balancing the robustness and convergence of tatonnement"):
  with members:
    - "a strongly polynomial algorithm for linear exchange markets"
    - "tracing equilibrium in dynamic markets via distributed adaptation"
    - "amortized analysis of asynchronous price dynamics"
    - "tatonnement in ongoing markets of complementary goods"
    - "the complexity of non monotone markets"
    - "a combinatorial polynomial algorithm for the linear arrow debreu market"
    - "settling the complexity of arrow debreu equilibria in markets with additively separable utilities"

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"
    - "nash social welfare approximation for strategic agents"
    - "a price anticipating resource allocation mechanism for distributed shared clusters"

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)