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: "reinforcement learning produces dominant strategies for the iterated prisoner s dilemma"
  Abstract: We present tournament results and several powerful strategies for the Iterated Prisoner’s Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and classic strategies. All the trained strategies win standard tournaments against the total collection of other opponents. The trained strategies and one particular human made designed strategy are the top performers in noisy tournaments also.

Connected through hyperedge HE-1 (induced by source paper "a meta analysis of tournaments and an evaluation of performance in the iterated prisoner s dilemma"):
  with members:
    - "re run repeat reproduce reuse replicate transforming code into scientific contributions"
    - "the numpy array a structure for efficient numerical computation"

Connected through hyperedge HE-2 (induced by source paper "stability of defection optimisation of strategies and the limits of memory in the prisoner s dilemma"):
  with members:
    - "re run repeat reproduce reuse replicate transforming code into scientific contributions"
    - "the numpy array a structure for efficient numerical computation"

Connected through hyperedge HE-3 (induced by source paper "learning multiagent coordination in the absence of communication channels"):
  with members:
    - "multi agent actor critic for mixed cooperative competitive environments"
    - "learning multiagent communication with backpropagation"
    - "empirically evaluating multiagent learning algorithms"
    - "empirical evaluation of gated recurrent neural networks on sequence modeling"

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)