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: "flows and decompositions of games harmonic and potential games"
  Abstract: In this paper we introduce a novel flow representation for finite games in strategic form. This representation allows us to develop a canonical direct sum decomposition of an arbitrary game into three components, which we refer to as the potential, harmonic, and nonstrategic components. We analyze natural classes of games that are induced by this decomposition, and in particular, focus on games with no harmonic component and games with no potential component. We show that the first class corresponds to the well-known potential games. We refer to the second class of games as harmonic games, and demonstrate that this new class has interesting properties which contrast with properties of potential games. Exploiting the decomposition framework, we obtain explicit expressions for the projections of games onto the subspaces of potential and harmonic games. This enables an extension of the equilibrium properties of potential and harmonic games to “nearby” games.

Connected through hyperedge HE-1 (induced by source paper "alpha rank multi agent evaluation by evolution"):
  with members:
    - "emergent coordination through competition"
    - "a generalised method for empirical game theoretic analysis"
    - "re evaluating evaluation"
    - "the exact computational complexity of evolutionarily stable strategies"
    - "learning dynamics and the co evolution of competing sexual species"
    - "multiplicative weights update with constant step size in congestion games convergence limit cycles and chaos"
    - "a unified game theoretic approach to multiagent reinforcement learning"
    - "deepstack expert level artificial intelligence in heads up no limit poker"

Connected through hyperedge HE-2 (induced by source paper "open ended learning in symmetric zero sum games"):
  with members:
    - "human level performance in 3d multiplayer games with population based reinforcement learning"
    - "paired open ended trailblazer poet endlessly generating increasingly complex and diverse learning environments and their solutions"
    - "the mechanics of n player differentiable games"
    - "emergent complexity via multi agent competition"
    - "a unified game theoretic approach to multiagent reinforcement learning"
    - "continuous adaptation via meta learning in nonstationary and competitive environments"
    - "curiosity driven exploration by self supervised prediction"

Connected through hyperedge HE-3 (induced by source paper "equilibrium characterization for data acquisition games"):
  with members:
    - "a game theoretic approach to recommendation systems with strategic content providers"
    - "competing bandits learning under competition"
    - "the value of sharing intermittent spectrum"

Connected through hyperedge HE-4 (induced by source paper "pure nash equilibria and best response dynamics in random games"):
  with members:
    - "best response dynamics in combinatorial auctions with item bidding"
    - "on the structure of weakly acyclic games"

Connected through hyperedge HE-5 (induced by source paper "decomposition of games some strategic considerations"):
  with members:
    - "hodge decomposition and the shapley value of a cooperative game"

Connected through hyperedge HE-6 (induced by source paper "hodge decomposition and the shapley value of a cooperative game"):
  with members:
    - "least squares ranking on graphs"

Connected through hyperedge HE-7 (induced by source paper "the mechanics of n player differentiable games"):
  with members:
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "strongly typed agents are guaranteed to interact safely"
    - "feudal networks for hierarchical reinforcement learning"
    - "the numerics of gans"
    - "cycles in adversarial regularized learning"
    - "gradient descent gan optimization is locally stable"
    - "curiosity driven exploration by self supervised prediction"
    - "training gans with optimism"

Connected through hyperedge HE-8 (induced by source paper "the buck passing game"):
  with members:
    - "interdependent values without single crossing"
    - "a variational inequality framework for network games existence uniqueness convergence and sensitivity analysis"
    - "location games on networks existence and efficiency of equilibria"
    - "pagerank beyond the web"
    - "approximate revenue maximization in interdependent value settings"
    - "graphical models for game theory"
    - "maximizing pagerank via outlinks"

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)