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: "qualitative models for decision under uncertainty without the commensurability assumption"
  Abstract: This paper investigates a purely qualitative version of Savage's theory for decision making under uncertainty. Until now, most representation theorems for preference over acts rely on a numerical representation of utility and uncertainty where utility and uncertainty are commensurate. Disrupting the tradition, we relax this assumption and introduce a purely ordinal axiom requiring that the Decision Maker (DM) preference between two acts only depends on the relative position of their consequences for each state. Within this qualitative framework, we determine the only possible form of the decision rule and investigate some instances compatible with the transitivity of the strict preference. Finally we propose a mild relaxation of our ordinality axiom, leaving room for a new family of qualitative decision rules compatible with transitivity.

Connected through hyperedge HE-1 (induced by source paper "on the complexity of decision making in possibilistic decision trees"):
  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"
    - "a comparison of axiomatic approaches to qualitative decision making using possibility theory"

Connected through hyperedge HE-2 (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"
    - "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"
    - "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)