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: "conditional plausibility measures and bayesian networks"
  Abstract: A general notion of algebraic conditional plausibility measures is defined. Probability measures, ranking functions, possibility measures, and (under the appropriate definitions) sets of probability measures can all be viewed as defining algebraic conditional plausibility measures. It is shown that algebraic conditional plausibility measures can be represented using Bayesian networks.

Connected through hyperedge HE-1 (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"
    - "plausibility measures and default reasoning"

Connected through hyperedge HE-2 (induced by source paper "an algebraic graphical model for decision with uncertainties feasibilities and utilities"):
  with members:
    - "a possibilistic model for qualitative sequential decision problems under uncertainty in partially observable environments"
    - "qualitative models for decision under uncertainty without the commensurability assumption"
    - "an order of magnitude calculus"
    - "graphical models for preference and utility"
    - "plausibility measures a user s guide"
    - "a qualitative linear utility theory for spohn s theory of epistemic beliefs"
    - "context specific independence in bayesian networks"
    - "a general non probabilistic theory of inductive reasoning"

Connected through hyperedge HE-3 (induced by source paper "great expectations part ii generalized expected utility as a universal decision rule"):
  with members:
    - "plausibility measures a user s guide"
    - "a comparison of axiomatic approaches to qualitative decision making using possibility theory"
    - "great expectations part i on the customizability of generalized expected utility"
    - "expected qualitative utility maximization"

Connected through hyperedge HE-4 (induced by source paper "great expectations part i on the customizability of generalized expected utility"):
  with members:
    - "generalized qualitative probability savage revisited"
    - "plausibility measures a user s guide"
    - "a comparison of axiomatic approaches to qualitative decision making using possibility theory"
    - "great expectations part ii generalized expected utility as a universal decision rule"

Connected through hyperedge HE-5 (induced by source paper "secrecy in multiagent systems"):
  with members:
    - "plausibility measures and default reasoning"

Connected through hyperedge HE-6 (induced by source paper "plausibility measures and default reasoning"):
  with members:
    - "plausibility measures a user s guide"
    - "a qualitative markov assumption and its implications for belief change"
    - "general belief measures"
    - "from statistical knowledge bases to degrees of belief"
    - "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)