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 "optimal dynamic information provision in traffic routing"):
  Abstract: We consider a two-road dynamic routing game where the state of one of the roads (the "risky road") is stochastic and may change over time. This generates room for experimentation. A central planner may wish to induce some of the (finite number of atomic) agents to use the risky road even when the expected cost of travel there is high in order to obtain accurate information about the state of the road. Since agents are strategic, we show that in order to generate incentives for experimentation the central planner however needs to limit the number of agents using the risky road when the expected cost of travel on the risky road is low. In particular, because of congestion, too much use of the risky road when the state is favorable would make experimentation no longer incentive compatible. We characterize the optimal incentive compatible recommendation system, first in a two-stage game and then in an infinite-horizon setting. In both cases, this system induces only partial, rather than full, information sharing among the agents (otherwise there would be too much exploitation of the risky road when costs there are low).

Includes members:
  Member "bandit learning with positive externalities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adaptive sequential experiments with unknown information flows")
  Member "effects of information heterogeneity in bayesian routing games":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "uncertainty in multi commodity routing networks when does it help")
  Member "dynamic routing for social information sharing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crowd mecs a novel crowdsourcing framework for mobile edge caching and sharing")
  Member "informational braess paradox the effect of information on traffic congestion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "signaling in bayesian network congestion games the subtle power of symmetry")
  Member "matching while learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "competing bandits in matching markets")

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)