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: "great expectations part i on the customizability of generalized expected utility"
  Abstract: We propose a generalization of expected utility that we call generalized EU (GEU), where a decision maker's beliefs are represented by plausibility measures, and the decision maker's tastes are represented by general (i.e.,not necessarily real-valued) utility functions. We show that every agent, ``rational'' or not, can be modeled as a GEU maximizer. We then show that we can customize GEU by selectively imposing just the constraints we want. In particular, we show how each of Savage's postulates corresponds to constraints on GEU.

Connected through hyperedge HE-1 (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 qualitative linear utility theory for spohn s theory of epistemic beliefs"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "reasoning about uncertainty in metric spaces"):
  with members:
    - "reasoning about expectation"
    - "great expectations part ii generalized expected utility as a universal decision rule"

Connected through hyperedge HE-3 (induced by source paper "a new axiomatization for likelihood gambles"):
  with members:
    - "statistical decisions using likelihood information without prior probabilities"
    - "great expectations part ii generalized expected utility as a universal decision rule"

Connected through hyperedge HE-4 (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-5 (induced by source paper "characterizing solution concepts in games using knowledge based programs"):
  with members:
    - "regret minimizing equilibria and mechanisms for games with strict type uncertainty"
    - "extensive games with possibly unaware players"
    - "using counterfactuals in knowledge based programming"

Connected through hyperedge HE-6 (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"
    - "expected qualitative utility maximization"
    - "conditional plausibility measures and bayesian networks"

Connected through hyperedge HE-7 (induced by source paper "characterizing and reasoning about probabilistic and non probabilistic expectation"):
  with members:
    - "reasoning about expectation"
    - "a logic for reasoning about upper probabilities"
    - "great expectations part ii generalized expected utility as a universal decision rule"

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)