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 "stackelberg pricing is hard to approximate within 2 epsilon"):
  Abstract: Stackelberg Pricing Games is a two-level combinatorial pricing problem studied in the Economics, Operation Research, and Computer Science communities. In this paper, we consider the decade-old shortest path version of this problem which is the first and most studied problem in this family. #R##N#The game is played on a graph (representing a network) consisting of {\em fixed cost} edges and {\em pricable} or {\em variable cost} edges. The fixed cost edges already have some fixed price (representing the competitor's prices). Our task is to choose prices for the variable cost edges. After that, a client will buy the cheapest path from a node $s$ to a node $t$, using any combination of fixed cost and variable cost edges. The goal is to maximize the revenue on variable cost edges. #R##N#In this paper, we show that the problem is hard to approximate within $2-\epsilon$, improving the previous \APX-hardness result by Joret [to appear in {\em Networks}]. Our technique combines the existing ideas with a new insight into the price structure and its relation to the hardness of the instances.

Includes members:
  Member "the stackelberg minimum spanning tree game on planar and bounded treewidth graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "specializations and generalizations of the stackelberg minimum spanning tree game")
  Member "the stackelberg minimum spanning tree game":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "negative prices in network pricing games")
  Member "stackelberg network pricing is hard to approximate":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "negative prices in network pricing games")
  Member "improved hardness of approximation for stackelberg shortest path pricing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "negative prices in network pricing games")
  Member "stackelberg network pricing games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "negative prices in network pricing games")

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)