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: "the complexity of the homotopy method equilibrium selection and lemke howson solutions"
  Abstract: We show that the widely used homotopy method for solving fixpoint problems, as well as the Harsanyi-Selten equilibrium selection process for games, are PSPACE-complete to implement. Extending our result for the Harsanyi-Selten process, we show that several other homotopy-based algorithms for finding equilibria of games are also PSPACE-complete to implement. A further application of our techniques yields the result that it is PSPACE-complete to compute any of the equilibria that could be found via the classical Lemke-Howson algorithm, a complexity-theoretic strengthening of the result in [Savani and von Stengel]. These results show that our techniques can be widely applied and suggest that the PSPACE-completeness of implementing homotopy methods is a general principle.

Connected through hyperedge HE-1 (induced by source paper "a generalized training approach for multiagent learning"):
  with members:
    - "evolutionary reinforcement learning for sample efficient multiagent coordination"
    - "multiagent evaluation under incomplete information"
    - "emergent coordination through competition"
    - "a survey and critique of multiagent deep reinforcement learning"
    - "openspiel a framework for reinforcement learning in games"
    - "human level performance in 3d multiplayer games with population based reinforcement learning"
    - "open ended learning in symmetric zero sum games"
    - "actor attention critic for multi agent reinforcement learning"

Connected through hyperedge HE-2 (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-3 (induced by source paper "on the computational power of online gradient descent"):
  with members:
    - "introduction to online convex optimization"
    - "stochastic gradient descent performs variational inference converges to limit cycles for deep networks"
    - "on the computational complexity of limit cycles in dynamical systems"
    - "on simplex pivoting rules and complexity theory"
    - "the complexity of the simplex method"
    - "the simplex algorithm is np mighty"

Connected through hyperedge HE-4 (induced by source paper "complexity and parametric computation of equilibria in atomic splittable congestion games via weighted block laplacians"):
  with members:
    - "computing all wardrop equilibria parametrized by the flow demand"
    - "uniqueness of equilibria in atomic splittable polymatroid congestion games"
    - "computing solutions of the multiclass network equilibrium problem with affine cost functions"
    - "constant rank bimatrix games are ppad hard"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-5 (induced by source paper "the power allocation game on a network computation issue"):
  with members:
    - "countries survival in networked international environments"
    - "game of power allocation on networks"

Connected through hyperedge HE-6 (induced by source paper "an empirical study of finding approximate equilibria in bimatrix games"):
  with members:
    - "unit vector games"
    - "ranking games that have competitiveness based strategies"
    - "polylogarithmic supports are required for approximate well supported nash equilibria below 2 3"
    - "combining local search techniques and path following for bimatrix games"
    - "approximate well supported nash equilibria below two thirds"
    - "an experimental analysis of lemke howson algorithm"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-7 (induced by source paper "the complexity of all switches strategy improvement"):
  with members:
    - "on simplex pivoting rules and complexity theory"
    - "the complexity of the simplex method"
    - "the simplex algorithm is np mighty"
    - "an exponential lower bound for the latest deterministic strategy iteration algorithms"
    - "non oblivious strategy improvement"
    - "exponential lower bounds for policy iteration"
    - "linear complementarity algorithms for infinite games"

Connected through hyperedge HE-8 (induced by source paper "unit vector games"):
  with members:
    - "oriented euler complexes and signed perfect matchings"

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)