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: "games on graphs with a public signal monitoring"
  Abstract: We study Nash equilibria in games on graphs with an imperfect monitoring based on a public signal. In such games, deviations and players responsible for those deviations can be hard to detect and track. We propose a generic epistemic game abstraction, which conveniently allows to represent the knowledge of the players about these deviations, and give a characterization of Nash equilibria in terms of winning strategies in the abstraction. We then use the abstraction to develop algorithms for some payoff functions.

Connected through hyperedge HE-1 (induced by source paper "reachability games in dynamic epistemic logic"):
  with members:
    - "reasoning about knowledge and strategies under hierarchical information"
    - "cooperative epistemic multi agent planning for implicit coordination"
    - "hanabi is np complete even for cheaters who look at their cards"
    - "hanabi is np hard even for cheaters who look at their cards"
    - "hierarchical information and the synthesis of distributed strategies"
    - "automata techniques for epistemic protocol synthesis"
    - "the computational complexity of probabilistic planning"

Connected through hyperedge HE-2 (induced by source paper "nash equilibria in games over graphs equipped with a communication mechanism"):
  with members:
    - "the complexity of nash equilibria in limit average games"

Connected through hyperedge HE-3 (induced by source paper "strategy logic with imperfect information"):
  with members:
    - "decidability results for atl with imperfect information and perfect recall"
    - "the fixed initial credit problem for partial observation energy games is ack complete"
    - "hierarchical information and the synthesis of distributed strategies"
    - "hierarchical information patterns and distributed strategy synthesis"
    - "pure nash equilibria in concurrent deterministic games"
    - "atlsc with partial observation"
    - "games with a weak adversary"
    - "mcmas slk a model checker for the verification of strategy logic specifications"

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)