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 "optimal mechanisms for distributed resource allocation"):
  Abstract: As the complexity of real-world systems continues to increase, so does the need for distributed protocols that are capable of guaranteeing a satisfactory system performance, without the reliance on centralized decision making. In this respect, game theory provides a valuable framework for the design of distributed algorithms in the form of equilibrium efficiency bounds. Arguably one of the most widespread performance metrics, the price-of-anarchy measures how the efficiency of a system degrades when moving from centralized to distributed decision making. While the smoothness framework -- introduced in Roughgarden 2009 -- has emerged as a powerful methodology for bounding the price-of-anarchy, the resulting bounds are often conservative, bringing into question the suitability of the smoothness approach for the design of distributed protocols. In this paper, we introduce the notion of generalized smoothness in order to overcome these difficulties. First, we show that generalized smoothness arguments are more widely applicable, and provide tighter price-of-anarchy bounds compared to those obtained using the existing smoothness framework. Second, we show how to leverage the notion of generalized smoothness to obtain a tight characterization of the price-of-anarchy, relative to the class of local cost-sharing games. Within this same class of games we show that the price-of-anarchy can be computed and optimized through the solution of a tractable linear program. Finally, we demonstrate that our approach subsumes and generalizes existing results for three well-studied classes of games.

Includes members:
  Member "tight approximation bounds for maximum multi coverage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "utility design for distributed resource allocation part i characterizing and optimizing the exact price of anarchy")
  Member "optimal price of anarchy in cost sharing games":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "when smoothness is not enough toward exact quantification and optimization of the price of anarchy")
  Member "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "when smoothness is not enough toward exact quantification and optimization of the price of anarchy")
  Member "intense competition can drive selfish explorers to optimize coverage":
    also connected through other hyperedges:
      (none)
  Member "distributed resource allocation through utility design part ii applications to submodular supermodular and set covering problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multiagent maximum coverage problems the trade off between anarchy and stability")
  Member "multiagent maximum coverage problems the trade off between anarchy and stability":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "when smoothness is not enough toward exact quantification and optimization of the price of anarchy")
  Member "learning in games robustness of fast convergence":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bandits with adversarial scaling")
  Member "a market inspired approach for intersection management in urban road traffic networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coordination of autonomous vehicles taxonomy and survey")

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)