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 "from poincar e recurrence to convergence in imperfect information games finding equilibrium via regularization"):
  Abstract: In this paper we investigate the Follow the Regularized Leader dynamics in sequential imperfect information games (IIG). We generalize existing results of Poincare recurrence from normal-form games to zero-sum two-player imperfect information games and other sequential game settings. We then investigate how adapting the reward (by adding a regularization term) of the game can give strong convergence guarantees in monotone games. We continue by showing how this reward adaptation technique can be leveraged to build algorithms that converge exactly to the Nash equilibrium. Finally, we show how these insights can be directly used to build state-of-the-art model-free algorithms for zero-sum two-player Imperfect Information Games (IIG).

Includes members:
  Member "from darwin to poincar e and von neumann recurrence and cycles in evolutionary and algorithmic game theory":
    also connected through other hyperedges:
      (none)
  Member "computing approximate equilibria in sequential adversarial games by exploitability descent":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "openspiel a framework for reinforcement learning in games")
  Member "a theory of regularized markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "provably efficient exploration for rl with unsupervised learning")
  Member "openspiel a framework for reinforcement learning in games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "accelerating and improving alphazero using population based training")
  Member "impala scalable distributed deep rl with importance weighted actor learner architectures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "explore discover and learn unsupervised discovery of state covering skills")
  Member "the mechanics of n player differentiable games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "smooth markets a basic mechanism for organizing gradient based learners")
  Member "stable opponent shaping in differentiable games":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimizing millions of hyperparameters by implicit differentiation")
  Member "modeling friends and foes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "meta learning of sequential strategies")

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)