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: "plausibility measures and default reasoning"
  Abstract: We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility measures. We focus on one application of plausibility measures in this paper: default reasoning. In recent years, a number of different semantics for defaults have been proposed, such as preferential structures, $\epsilon$-semantics, possibilistic structures, and $\kappa$-rankings, that have been shown to be characterized by the same set of axioms, known as the KLM properties. While this was viewed as a surprise, we show here that it is almost inevitable. In the framework of plausibility measures, we can give a necessary condition for the KLM axioms to be sound, and an additional condition necessary and sufficient to ensure that the KLM axioms are complete. This additional condition is so weak that it is almost always met whenever the axioms are sound. In particular, it is easily seen to hold for all the proposals made in the literature.

Connected through hyperedge HE-1 (induced by source paper "a reconstruction of the multipreference closure"):
  with members:
    - "reasoning about exceptions in ontologies from the lexicographic closure to the skeptical closure"
    - "reasoning about multiple aspects in dls semantics and closure construction"
    - "analytic tableaux calculi for klm logics of nonmonotonic reasoning"
    - "what does a conditional knowledge base entail"
    - "another perspective on default reasoning"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-2 (induced by source paper "cause responsibility and blame oa structural model approach"):
  with members:
    - "axiomatizing causal reasoning"
    - "actual causation and the art of modeling"
    - "defaults and normality in causal structures"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-3 (induced by source paper "defining relative likelihood in partially ordered preferential structures"):
  with members:
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-4 (induced by source paper "compact representations of extended causal models"):
  with members:
    - "axiomatizing causal reasoning"
    - "plausibility measures a user s guide"
    - "graded causation and defaults"
    - "actual causation and the art of modeling"
    - "defaults and normality in causal structures"
    - "nonmonotonic reasoning preferential models and cumulative logics"
    - "conditional plausibility measures and bayesian networks"

Connected through hyperedge HE-5 (induced by source paper "plausibility measures a user s guide"):
  with members:
    - "a qualitative markov assumption and its implications for belief change"
    - "general belief measures"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-6 (induced by source paper "a qualitative markov assumption and its implications for belief change"):
  with members:
    - "numerical representations of acceptance"
    - "general belief measures"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-7 (induced by source paper "comparative uncertainty belief functions and accepted beliefs"):
  with members:
    - "generalized qualitative probability savage revisited"
    - "decision making under ordinal preferences and comparative uncertainty"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-8 (induced by source paper "decision making under ordinal preferences and comparative uncertainty"):
  with members:
    - "generalized qualitative probability savage revisited"
    - "what does a conditional knowledge base entail"
    - "nonmonotonic reasoning preferential models and cumulative logics"

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.AI(Artificial Intelligence)