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: "on the complexity of dynamic mechanism design"
  Abstract: We introduce a dynamic mechanism design problem in which the designer wants to offer for sale an item to an agent, and another item to the same agent at some point in the future. The agent's joint distribution of valuations for the two items is known, and the agent knows the valuation for the current item (but not for the one in the future). The designer seeks to maximize expected revenue, and the auction must be deterministic, truthful, and ex post individually rational. The optimum mechanism involves a protocol whereby the seller elicits the buyer's current valuation, and based on the bid makes two take-it-or-leave-it offers, one for now and one for the future. We show that finding the optimum deterministic mechanism in this situation - arguably the simplest meaningful dynamic mechanism design problem imaginable - is NP-hard. We also prove several positive results, among them a polynomial linear programming-based algorithm for the optimum randomized auction (even for many bidders and periods), and we show strong separations in revenue between non-adaptive, adaptive, and randomized auctions, even when the valuations in the two periods are uncorrelated. Finally, for the same problem in an environment in which contracts cannot be enforced, and thus perfection of equilibrium is necessary, we show that the optimum randomized mechanism requires multiple rounds of cheap talk-like interactions.

Connected through hyperedge HE-1 (induced by source paper "dynamic first price auctions robust to heterogeneous buyers"):
  with members:
    - "robust repeated auctions under heterogeneous buyer behavior"
    - "selling to a no regret buyer"
    - "sequential mechanisms with ex post participation guarantees"
    - "perfect bayesian equilibria in repeated sales"
    - "online bandit learning against an adaptive adversary from regret to policy regret"

Connected through hyperedge HE-2 (induced by source paper "monopoly pricing with buyer search"):
  with members:
    - "planning with multiple biases"
    - "on the value of penalties in time inconsistent planning"
    - "revenue gaps for discriminatory and anonymous sequential posted pricing"
    - "the menu size complexity of revenue approximation"
    - "efficient empirical revenue maximization in single parameter auction environments"
    - "sampling and representation complexity of revenue maximization"
    - "time inconsistent planning a computational problem in behavioral economics"
    - "combinatorial auctions via posted prices"

Connected through hyperedge HE-3 (induced by source paper "robust repeated auctions under heterogeneous buyer behavior"):
  with members:
    - "optimal dynamic mechanisms with ex post ir via bank accounts"
    - "online bandit learning against an adaptive adversary from regret to policy regret"

Connected through hyperedge HE-4 (induced by source paper "optimal dynamic auctions are virtual welfare maximizers"):
  with members:
    - "simple mechanisms for subadditive buyers via duality"
    - "optimal dynamic mechanisms with ex post ir via bank accounts"

Connected through hyperedge HE-5 (induced by source paper "selling to a no regret buyer"):
  with members:
    - "learning multi item auctions with or without samples"
    - "on the competition complexity of dynamic mechanism design"
    - "learning simple auctions"
    - "efficient empirical revenue maximization in single parameter auction environments"
    - "sequential mechanisms with ex post participation guarantees"
    - "optimal dynamic mechanisms with ex post ir via bank accounts"
    - "the sample complexity of revenue maximization"
    - "the sample complexity of auctions with side information"

Connected through hyperedge HE-6 (induced by source paper "on the competition complexity of dynamic mechanism design"):
  with members:
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for subadditive buyers via duality"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "optimal dynamic mechanisms with ex post ir via bank accounts"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "strong duality for a multiple good monopolist"

Connected through hyperedge HE-7 (induced by source paper "revenue maximization with an uncertainty averse buyer"):
  with members:
    - "prior independent auctions for risk averse agents"

Connected through hyperedge HE-8 (induced by source paper "optimal dynamic mechanisms with ex post ir via bank accounts"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "sequential mechanisms with ex post participation guarantees"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "the menu size complexity of auctions"
    - "an algorithmic characterization of multi dimensional mechanisms"

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)