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: "asymptotically tight bounds for inefficiency in risk averse selfish routing"
  Abstract: We consider a nonatomic selfish routing model with independent stochastic travel times, represented by mean and variance latency functions for each edge that depend on their flows. In an effort to decouple the effect of risk-averse player preferences from selfish behavior on the degradation of system performance, Nikolova and Stier- Moses [16] defined the concept of the price of risk aversion as the worst-case ratio of the cost of an equilibrium with risk-averse players and that of an equilibrium with risk-neutral users. For risk-averse users who seek to minimize the mean plus variance of travel time on a path, they proved an upper bound on the price of risk aversion, which is independent of the latency functions, and grows linearly with the size of the graph and players' risk-aversion. In this follow-up paper, we provide a matching lower bound for graphs with number of vertices equal to powers of two, via the construction of a graph family inductively generated from the Braess graph. We also provide conceptually different bounds, which we call functional, that depend on the class of mean latency functions and provide characterizations that are independent of the network topology (first derived, in a more complicated way, by Meir and Parkes [10] in a different context with different techniques). We also supplement the upper bound with a new asymptotically-tight lower bound. Our third contribution is a tight bound on the price of risk aversion for a family of graphs that generalize series-parallel graphs which applies to users minimizing the mean plus standard deviation of a path, a much more complex model of risk-aversion due to the cost of a path being non-additive over edge costs. This is a refinement of previous results in [16] that characterized the price of risk-aversion for series-parallel graphs and for the Braess graph.

Connected through hyperedge HE-1 (induced by source paper "can taxes improve congestion on all networks"):
  with members:
    - "path deviations outperform approximate stability in heterogeneous congestion games"
    - "achieving target equilibria in network routing games without knowing the latency functions"
    - "playing the wrong game smoothness bounds for congestion games with behavioral biases"
    - "potential games are necessary to ensure pure nash equilibria in cost sharing games"

Connected through hyperedge HE-2 (induced by source paper "directed graph minors and serial parallel width"):
  with members:
    - "the burden of risk aversion in mean risk selfish routing"
    - "time inconsistent planning a computational problem in behavioral economics"
    - "a complete anytime algorithm for treewidth"

Connected through hyperedge HE-3 (induced by source paper "directed graph embeddings"):
  with members:
    - "informational braess paradox the effect of information on traffic congestion"
    - "playing the wrong game smoothness bounds for congestion games with heterogeneous biases"
    - "computational issues in time inconsistent planning"
    - "time inconsistent planning a computational problem in behavioral economics"
    - "a complete anytime algorithm for treewidth"

Connected through hyperedge HE-4 (induced by source paper "path deviations outperform approximate stability in heterogeneous congestion games"):
  with members:
    - "the impact of worst case deviations in non atomic network routing games"
    - "matroids are immune to braess paradox"
    - "the burden of risk aversion in mean risk selfish routing"
    - "on the performance of approximate equilibria in congestion games"

Connected through hyperedge HE-5 (induced by source paper "the price of anarchy in auctions"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "best response dynamics in combinatorial auctions with item bidding"
    - "simple mechanisms for agents with complements"
    - "the price of anarchy in large games"
    - "on the economic efficiency of the combinatorial clock auction"
    - "on the efficiency of all pay mechanisms"
    - "learning and efficiency in games with dynamic population"
    - "no regret learning in bayesian games"

Connected through hyperedge HE-6 (induced by source paper "the impact of worst case deviations in non atomic network routing games"):
  with members:
    - "path deviations outperform approximate stability in heterogeneous congestion games"
    - "the burden of risk aversion in mean risk selfish routing"
    - "congestion games with distance based strict uncertainty"
    - "playing the wrong game smoothness bounds for congestion games with behavioral biases"
    - "on the performance of approximate equilibria in congestion games"

Connected through hyperedge HE-7 (induced by source paper "playing the wrong game smoothness bounds for congestion games with behavioral biases"):
  with members:
    - "the price of anarchy in large games"
    - "the burden of risk aversion in mean risk selfish routing"
    - "congestion games with distance based strict uncertainty"
    - "improving the price of anarchy for selfish routing via coordination mechanisms"
    - "the robust price of anarchy of altruistic games"

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)