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: "independence concepts for convex sets of probabilities"
  Abstract: In this paper we study different concepts of independence for convex sets of probabilities. There will be two basic ideas for independence. The first is irrelevance. Two variables are independent when a change on the knowledge about one variable does not affect the other. The second one is factorization. Two variables are independent when the joint convex set of probabilities can be decomposed on the product of marginal convex sets. In the case of the Theory of Probability, these two starting points give rise to the same definition. In the case of convex sets of probabilities, the resulting concepts will be strongly related, but they will not be equivalent. As application of the concept of independence, we shall consider the problem of building a global convex set from marginal convex sets of probabilities.

Connected through hyperedge HE-1 (induced by source paper "weighted regret based likelihood a new approach to describing uncertainty"):
  with members:
    - "defining relative likelihood in partially ordered preferential structures"
    - "a logic for reasoning about upper probabilities"
    - "do we need higher order probabilities and if so what do they mean"
    - "calculating uncertainty intervals from conditional convex sets of probabilities"
    - "weighted sets of probabilities and minimaxweighted expected regret new approaches for representing uncertainty and making decisions"

Connected through hyperedge HE-2 (induced by source paper "separation properties of sets of probability measures"):
  with members:
    - "independence with lower and upper probabilities"
    - "robustness analysis of bayesian networks with local convex sets of distributions"
    - "irrelevance and independence relations in quasi bayesian networks"

Connected through hyperedge HE-3 (induced by source paper "irrelevance and independence relations in quasi bayesian networks"):
  with members:
    - "independence with lower and upper probabilities"
    - "robustness analysis of bayesian networks with local convex sets of distributions"
    - "decision making with interval influence diagrams"

Connected through hyperedge HE-4 (induced by source paper "independence with lower and upper probabilities"):
  with members:
    - "a new approach to updating beliefs"
    - "quasi bayesian strategies for efficient plan generation application to the planning to observe problem"

Connected through hyperedge HE-5 (induced by source paper "strategy selection in influence diagrams using imprecise probabilities"):
  with members:
    - "probabilistic inference in influence diagrams"
    - "from influence diagrams to junction trees"
    - "complexity results and approximation strategies for map explanations"

Connected through hyperedge HE-6 (induced by source paper "irrelevant and independent natural extension for sets of desirable gambles"):
  with members:
    - "epistemic irrelevance in credal nets the case of imprecise markov trees"

Connected through hyperedge HE-7 (induced by source paper "conditional plausibility measures and bayesian networks"):
  with members:
    - "plausibility measures a user s guide"
    - "separation properties of sets of probability measures"
    - "on the logic of causal models"
    - "general belief measures"
    - "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"

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)