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: "a qualitative linear utility theory for spohn s theory of epistemic beliefs"
  Abstract: In this paper, we formulate a qualitative "linear" utility theory for lotteries in which uncertainty is expressed qualitatively using a Spohnian disbelief function. We argue that a rational decision maker facing an uncertain decision problem in which the uncertainty is expressed qualitatively should behave so as to maximize "qualitative expected utility." Our axiomatization of the qualitative utility is similar to the axiomatization developed by von Neumann and Morgenstern for probabilistic lotteries. We compare our results with other recent results in qualitative decision making.

Connected through hyperedge HE-1 (induced by source paper "a comparison of axiomatic approaches to qualitative decision making using possibility theory"):
  with members:
    - "a general non probabilistic theory of inductive reasoning"

Connected through hyperedge HE-2 (induced by source paper "axiomatic foundations for a class of generalized expected utility algebraic expected utility"):
  with members:
    - "an order of magnitude calculus"
    - "plausibility measures a user s guide"
    - "a general non probabilistic theory of inductive reasoning"
    - "general belief measures"
    - "a comparison of axiomatic approaches to qualitative decision making using possibility theory"
    - "decision making for symbolic probability"
    - "qualitative decision making under possibilistic uncertainty toward more discriminating criteria"
    - "decision making with partially consonant belief functions"

Connected through hyperedge HE-3 (induced by source paper "qualitative mdps and pomdps an order of magnitude approximation"):
  with members:
    - "a possibilistic model for qualitative sequential decision problems under uncertainty in partially observable environments"
    - "an order of magnitude calculus"
    - "a general non probabilistic theory of inductive reasoning"
    - "from conditional oughts to qualitative decision theory"
    - "value function approximations for partially observable markov decision processes"
    - "conformant planning via symbolic model checking"

Connected through hyperedge HE-4 (induced by source paper "statistical decisions using likelihood information without prior probabilities"):
  with members:
    - "a comparison of axiomatic approaches to qualitative decision making using possibility theory"

Connected through hyperedge HE-5 (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"
    - "context specific independence in bayesian networks"
    - "a general non probabilistic theory of inductive reasoning"
    - "general belief measures"

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)