human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "monopoly pricing with buyer search"):
  Abstract: In many shopping scenarios, e.g., in online shopping, customers have a large menu of options to choose from. However, most of the buyers do not browse all the options and make decision after considering only a small part of the menu. To study such buyer's behavior we consider the standard Bayesian monopoly problem for a unit-demand buyer, where the monopolist displays the menu dynamically page after a page to the buyer. The seller aims to maximize the expected revenue over the distribution of buyer's values which we assume are i.i.d. The buyer incurs a fixed cost for browsing through one menu page and would stop if that cost exceeds the increase in her utility. We observe that the optimal posted price mechanism in our dynamic setting may have quite different structure than in the classic static scenario. We find a (relatively) simple and approximately optimal mechanism, that uses part of the items as a "bait" to keep the buyer interested for multiple rounds with low prices, while at the same time showing many other expensive items.

Includes members:
  Member "planning with multiple biases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "on the value of penalties in time inconsistent planning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "revenue gaps for discriminatory and anonymous sequential posted pricing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tight revenue gaps among simple mechanisms")
  Member "the menu size complexity of revenue approximation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of contracts")
  Member "efficient empirical revenue maximization in single parameter auction environments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "sampling and representation complexity of revenue maximization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "time inconsistent planning a computational problem in behavioral economics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "time inconsistent planning simple motivation is hard to find")
  Member "on the complexity of dynamic mechanism design":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic first price auctions robust to heterogeneous buyers")

Question: Please tell me which class the source paper 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)