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: "myopic value of information in influence diagrams"
  Abstract: We present a method for calculation of myopic value of information in influence diagrams (Howard & Matheson, 1981) based on the strong junction tree framework (Jensen, Jensen & Dittmer, 1994). The difference in instantiation order in the influence diagrams is reflected in the corresponding junction trees by the order in which the chance nodes are marginalized. This order of marginalization can be changed by table expansion and in effect the same junction tree with expanded tables may be used for calculating the expected utility for scenarios with different instantiation order. We also compare our method to the classic method of modeling different instantiation orders in the same influence diagram.

Connected through hyperedge HE-1 (induced by source paper "value of information in probabilistic logic programs"):
  with members:
    - "an anytime algorithm for decision making under uncertainty"
    - "an approximate nonmyopic computation for value of information"
    - "near optimal nonmyopic value of information in graphical models"
    - "the pita system tabling and answer subsumption for reasoning under uncertainty"
    - "optimal value of information in graphical models"
    - "reasoning and planning with sensing actions incomplete information and static causal laws using answer set programming"
    - "parameter learning of logic programs for symbolic statistical modeling"
    - "cost sensitive classification empirical evaluation of a hybrid genetic decision tree induction algorithm"

Connected through hyperedge HE-2 (induced by source paper "practical context awareness measuring and utilizing the context dependency of mobile usage"):
  with members:
    - "near optimal nonmyopic value of information in graphical models"
    - "a longitudinal study of non voice mobile phone usage by teens from an underserved urban community"

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)