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: "groupthink and the failure of information aggregation in large groups"
  Abstract: We consider two Bayesian agents who learn from exogenously provided private signals, as well as the actions of the other. Our main finding is that increased interaction between the agents can lower the speed of learning: when both agents observe each other, learning is significantly slower than it is when one only observes the other. This slowdown is driven by a process in which a consensus on the wrong action causes the agents to discount new contrary evidence.

Connected through hyperedge HE-1 (induced by source paper "teaching and learning in uncertainty"):
  with members:
    - "bayesian heuristics for group decisions"
    - "the speed of social learning"

Connected through hyperedge HE-2 (induced by source paper "informational braess paradox the effect of information on traffic congestion"):
  with members:
    - "effects of information heterogeneity in bayesian routing games"
    - "matroids are immune to braess paradox"
    - "inducing approximately optimal flow using truthful mediators"
    - "the burden of risk aversion in mean risk selfish routing"
    - "when more information reduces the speed of learning"
    - "on the hardness of signaling"
    - "playing the wrong game smoothness bounds for congestion games with behavioral biases"

Connected through hyperedge HE-3 (induced by source paper "bayesian heuristics for group decisions"):
  with members:
    - "learning without recall a case for log linear learning"
    - "learning without recall by random walks on directed graphs"
    - "exponentially fast parameter estimation in networks using distributed dual averaging"

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)