human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "refining reasoning in qualitative probabilistic networks"):
  Abstract: In recent years there has been a spate of papers describing systems for probabilisitic reasoning which do not use numerical probabilities. In some cases the simple set of values used by these systems make it impossible to predict how a probability will change or which hypothesis is most likely given certain evidence. This paper concentrates on such situations, and suggests a number of ways in which they may be resolved by refining the representation.

Includes members:
  Member "on reasoning in networks with qualitative uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an order of magnitude calculus")
  Member "argumentative inference in uncertain and inconsistent knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "syntax based default reasoning as probabilistic model based diagnosis")
  Member "argument calculus and networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "action networks a framework for reasoning about actions and change under uncertainty")
  Member "an experimental comparison of numerical and qualitative probabilistic reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on transformations between probability and spohnian disbelief functions")
  Member "a symbolic approach to reasoning with linguistic quantifiers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "magic inference rules for probabilistic deduction under taxonomic knowledge")

Question: Please tell me which class the source paper 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)