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: "general belief measures"
  Abstract: Probability measures by themselves, are known to be inappropriate for modeling the dynamics of plain belief and their excessively strong measurability constraints make them unsuitable for some representational tasks, e.g. in the context of firstorder knowledge. In this paper, we are therefore going to look for possible alternatives and extensions. We begin by delimiting the general area of interest, proposing a minimal list of assumptions to be satisfied by any reasonable quasi-probabilistic valuation concept. Within this framework, we investigate two particularly interesting kinds of quasi-measures which are not or much less affected by the traditional problems. * Ranking measures, which generalize Spohn-type and possibility measures. * Cumulative measures, which combine the probabilistic and the ranking philosophy, allowing thereby a fine-grained account of static and dynamic belief.

Connected through hyperedge HE-1 (induced by source paper "a plausibility semantics for abstract argumentation frameworks"):
  with members:
    - "belief functions and default reasoning"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-2 (induced by source paper "defaults and infinitesimals defeasible inference by nonarchimedean entropy maximization"):
  with members:
    - "a general non probabilistic theory of inductive reasoning"
    - "the probability of a possibility adding uncertainty to default rules"
    - "what does a conditional knowledge base entail"
    - "another perspective on default reasoning"
    - "nonmonotonic reasoning preferential models and cumulative logics"

Connected through hyperedge HE-3 (induced by source paper "plausibility measures a user s guide"):
  with members:
    - "a qualitative markov assumption and its implications for belief change"
    - "nonmonotonic reasoning preferential models and cumulative logics"
    - "plausibility measures and default reasoning"

Connected through hyperedge HE-4 (induced by source paper "a qualitative markov assumption and its implications for belief change"):
  with members:
    - "numerical representations of acceptance"
    - "nonmonotonic reasoning preferential models and cumulative logics"
    - "plausibility measures and default reasoning"

Connected through hyperedge HE-5 (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"
    - "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-6 (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-7 (induced by source paper "conditional plausibility measures and bayesian networks"):
  with members:
    - "plausibility measures a user s guide"
    - "independence concepts for convex sets of probabilities"
    - "separation properties of sets of probability measures"
    - "on the logic of causal models"
    - "irrelevance and independence relations in quasi bayesian networks"
    - "conditional independence in possibility theory"
    - "on the relation between kappa calculus and probabilistic reasoning"
    - "an ordinal view of independence with application to plausible reasoning"

Connected through hyperedge HE-8 (induced by source paper "plausibility measures and default reasoning"):
  with members:
    - "plausibility measures a user s guide"
    - "a qualitative markov assumption and its implications for belief change"
    - "from statistical knowledge bases to degrees of belief"
    - "what does a conditional knowledge base entail"
    - "nonmonotonic reasoning preferential models and cumulative logics"
    - "conditional plausibility measures and bayesian networks"

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)