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: "complexity results about nash equilibria"
  Abstract: Noncooperative game theory provides a normative framework for analyzing strategic interactions. However, for the toolbox to be operational, the solutions it defines will have to be computed. In this paper, we provide a single reduction that 1) demonstrates NP-hardness of determining whether Nash equilibria with certain natural properties exist, and 2) demonstrates the #P-hardness of counting Nash equilibria (or connected sets of Nash equilibria). We also show that 3) determining whether a pure-strategy Bayes-Nash equilibrium exists is NP-hard, and that 4) determining whether a pure-strategy Nash equilibrium exists in a stochastic (Markov) game is PSPACE-hard even if the game is invisible (this remains NP-hard if the game is finite). All of our hardness results hold even if there are only two players and the game is symmetric. #R##N#Keywords: Nash equilibrium; game theory; computational complexity; noncooperative game theory; normal form game; stochastic game; Markov game; Bayes-Nash equilibrium; multiagent systems.

Connected through hyperedge HE-1 (induced by source paper "inference based strategy alignment for general sum differential games"):
  with members:
    - "on gradient based learning in continuous games"
    - "cooperation aware reinforcement learning for merging in dense traffic"
    - "on finding local nash equilibria and only local nash equilibria in zero sum games"
    - "on the convergence of gradient based learning in continuous games"
    - "social gan socially acceptable trajectories with generative adversarial networks"
    - "hierarchical game theoretic planning for autonomous vehicles"
    - "a scalable framework for real time multi robot multi human collision avoidance"
    - "the value of inferring the internal state of traffic participants for autonomous freeway driving"

Connected through hyperedge HE-2 (induced by source paper "the intrinsic robustness of stochastic bandits to strategic manipulation"):
  with members:
    - "online learning for measuring incentive compatibility in ad auctions"
    - "bayesian exploration with heterogeneous agents"
    - "stochastic bandits robust to adversarial corruptions"
    - "learning to bid without knowing your value"
    - "multi armed bandit problems with strategic arms"
    - "bayesian incentive compatible bandit exploration"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "analysis of thompson sampling for the multi armed bandit problem"

Connected through hyperedge HE-3 (induced by source paper "on relevant equilibria in reachability games"):
  with members:
    - "the complexity of subgame perfect equilibria in quantitative reachability games"
    - "constrained existence problem for weak subgame perfect equilibria with ω regular boolean objectives"
    - "computer aided synthesis a game theoretic approach"
    - "on subgame perfection in quantitative reachability games"
    - "multiplayer cost games with simple nash equilibria"

Connected through hyperedge HE-4 (induced by source paper "game theory explorer software for the applied game theorist"):
  with members:
    - "rank 1 games with exponentially many nash equilibria"

Connected through hyperedge HE-5 (induced by source paper "the complexity of computing a quasi perfect equilibrium for an n player extensive form game of perfect recall"):
  with members:
    - "the complexity of approximating a trembling hand perfect equilibrium of a multi player game in strategic form"

Connected through hyperedge HE-6 (induced by source paper "bounding the uncertainty of graphical games the complexity of simple requirements pareto and strong nash equilibria"):
  with members:
    - "graphical models for game theory"
    - "efficient nash computation in large population games with bounded influence"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-7 (induced by source paper "a sampling based approach to computing equilibria in succinct extensive form games"):
  with members:
    - "pegasus a policy search method for large mdps and pomdps"
    - "a continuation method for nash equilibria in structured games"

Connected through hyperedge HE-8 (induced by source paper "an efficient optimal equilibrium algorithm for two player game trees"):
  with members:
    - "graphical models for game theory"

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)