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: "utility based abstraction and categorization"
  Abstract: We take a utility-based approach to categorization. We construct generalizations about events and actions by considering losses associated with failing to distinguish among detailed distinctions in a decision model. The utility-based methods transform detailed states of the world into more abstract categories comprised of disjunctions of the states. We show how we can cluster distinctions into groups of distinctions at progressively higher levels of abstraction, and describe rules for decision making with the abstractions. The techniques introduce a utility-based perspective on the nature of concepts, and provide a means of simplifying decision models used in automated reasoning systems. We demonstrate the techniques by describing the capabilities and output of TUBA, a program for utility-based abstraction.

Connected through hyperedge HE-1 (induced by source paper "independence of causal influence and clique tree propagation"):
  with members:
    - "search based methods to bound diagnostic probabilities in very large belief nets"
    - "approximations in bayesian belief universe for knowledge based systems"
    - "causal independence for knowledge acquisition and inference"
    - "the use of conflicts in searching bayesian networks"
    - "a new look at causal independence"
    - "a generalization of the noisy or model"
    - "abstraction in belief networks the role of intermediate states in diagnostic reasoning"
    - "context specific independence in bayesian networks"

Connected through hyperedge HE-2 (induced by source paper "state space abstraction for anytime evaluation of probabilistic networks"):
  with members:
    - "approximations in bayesian belief universe for knowledge based systems"
    - "using tree decomposable structures to approximate belief networks"
    - "bounded conditioning flexible inference for decisions under scarce resources"
    - "ideal reformulation of belief networks"
    - "refinement and coarsening of bayesian networks"
    - "ideal a software package for analysis of influence diagrams"
    - "incremental probabilistic inference"

Connected through hyperedge HE-3 (induced by source paper "an anytime algorithm for decision making under uncertainty"):
  with members:
    - "decision making using probabilistic inference methods"
    - "reasoning about the value of decision model refinement methods and application"
    - "some properties of joint probability distributions"
    - "the compilation of decision models"
    - "flexible policy construction by information refinement"
    - "two procedures for compiling influence diagrams"

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)