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: "characterizing solution concepts in games using knowledge based programs"
  Abstract: We show how solution concepts in games such as Nash equilibrium, correlated equilibrium, rationalizability, and sequential equilibrium can be given a uniform definition in terms of \emph{knowledge-based programs}. Intuitively, all solution concepts are implementations of two knowledge-based programs, one appropriate for games represented in normal form, the other for games represented in extensive form. These knowledge-based programs can be viewed as embodying rationality. The representation works even if (a) information sets do not capture an agent's knowledge, (b) uncertainty is not represented by probability, or (c) the underlying game is not common knowledge.

Connected through hyperedge HE-1 (induced by source paper "characterizing solution concepts in terms of common knowledge of rationality"):
  with members:
    - "regret minimizing equilibria and mechanisms for games with strict type uncertainty"
    - "a logical characterization of iterated admissibility"
    - "lexicographic probability conditional probability and nonstandard probability"

Connected through hyperedge HE-2 (induced by source paper "from rules to runs a dynamic epistemic take on imperfect information games"):
  with members:
    - "a dynamic epistemic framework for conformant planning"
    - "a computer scientist looks at game theory"

Connected through hyperedge HE-3 (induced by source paper "an epistemic strategy logic"):
  with members:
    - "an epistemic strategy logic extended abstract"
    - "mcmas slk a model checker for the verification of strategy logic specifications"
    - "reasoning about knowledge and strategies epistemic strategy logic"
    - "reasoning about strategies under partial observability and fairness constraints"
    - "pdl as a multi agent strategy logic"
    - "model checking atl under imperfect information and perfect recall semantics is undecidable"
    - "knowledge and common knowledge in a distributed environment"

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)