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: "informational braess paradox the effect of information on traffic congestion"
  Abstract: To systematically study the implications of additional information about routes provided to certain users (e.g., via GPS-based route guidance systems), we introduce a new class of congestion games in which users have differing information sets about the available edges and can only use routes consisting of edges in their information set. After defining the notion of Information Constrained Wardrop Equilibrium (ICWE) for this class of congestion games and studying its basic properties, we turn to our main focus: whether additional information can be harmful (in the sense of generating greater equilibrium costs/delays). We formulate this question in the form of Informational Braes' Paradox (IBP), which extends the classic Braess' Paradox in traffic equilibria, and asks whether users receiving additional information can become worse off. We provide a comprehensive answer to this question showing that in any network in the series of linearly independent (SLI) class, which is a strict subset of series-parallel networks, IBP cannot occur, and in any network that is not in the SLI class, there exists a configuration of edge-specific cost functions for which IBP will occur. In the process, we establish several properties of the SLI class of networks, which include the characterization of the complement of the SLI class in terms of embedding a specific set of networks, and also an algorithm which determines whether a graph is SLI in linear time. We further prove that the worst-case inefficiency performance of ICWE is no worse than the standard Wardrop equilibrium.

Connected through hyperedge HE-1 (induced by source paper "signaling in bayesian network congestion games the subtle power of symmetry"):
  with members:
    - "bayesian persuasion with sequential games"
    - "on the tractability of public persuasion with no externalities"
    - "value of information systems in routing games"
    - "finding any nontrivial coarse correlated equilibrium is hard"
    - "a general framework for computing optimal correlated equilibria in compact games"

Connected through hyperedge HE-2 (induced by source paper "optimal dynamic information provision in traffic routing"):
  with members:
    - "bandit learning with positive externalities"
    - "effects of information heterogeneity in bayesian routing games"
    - "dynamic routing for social information sharing"
    - "matching while learning"

Connected through hyperedge HE-3 (induced by source paper "value of information in bayesian routing games"):
  with members:
    - "potential games are necessary to ensure pure nash equilibria in cost sharing games"

Connected through hyperedge HE-4 (induced by source paper "utilizing information optimally to influence distributed network routing"):
  with members:
    - "the importance of system level information in multiagent systems design cardinality and covering problems"
    - "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy"
    - "electric vehicle charging station network equilibrium models and pricing schemes"

Connected through hyperedge HE-5 (induced by source paper "reputation based information design for inducing prosocial behavior"):
  with members:
    - "energy coupon a mean field game perspective on demand response in smart grids"
    - "mean field games in nudge systems for societal networks"

Connected through hyperedge HE-6 (induced by source paper "on stability of users equilibria in heterogeneous routing games"):
  with members:
    - "on resilient control of dynamical flow networks"

Connected through hyperedge HE-7 (induced by source paper "social learning with questions"):
  with members:
    - "social learning with endogenous network formation"
    - "when is a network epidemic hard to eliminate"
    - "hypothesis testing in feedforward networks with broadcast failures"
    - "on learning with finite memory"
    - "strategic learning and the topology of social networks"

Connected through hyperedge HE-8 (induced by source paper "uncertainty in multi commodity routing networks when does it help"):
  with members:
    - "how much urban traffic is searching for parking"
    - "effects of information heterogeneity in bayesian routing games"
    - "to observe or not to observe queuing game framework for urban parking"
    - "power control in networks with heterogeneous users a quasi variational inequality approach"
    - "the burden of risk aversion in mean risk selfish routing"
    - "congestion games with distance based strict uncertainty"

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)