human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "credal networks under maximum entropy"):
  Abstract: We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. We then show that for all general Bayesian networks, the sequential maximum entropy model coincides with the unique joint distribution. Moreover, we apply the new principle of sequential maximum entropy to interval Bayesian networks and more generally to credal networks. We especially show that this application is equivalent to a number of small local entropy maximizations.

Includes members:
  Member "coherent knowledge processing at maximum entropy by spirit":
    also connected through other hyperedges:
      (none)
  Member "generating bayesian networks from probability logic knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "survey on models and techniques for root cause analysis")
  Member "decision making with interval influence diagrams":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robustness analysis of bayesian networks with local convex sets of distributions")
  Member "irrelevance and independence relations in quasi bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "separation properties of sets of probability measures")
  Member "from statistical knowledge bases to degrees of belief":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polynomial time probabilistic reasoning with partial observations via implicit learning in probability logics")
  Member "probabilistic default reasoning with conditional constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "epistemic graphs for representing and reasoning with positive and negative influences of arguments")
  Member "probabilistic deduction with conditional constraints over basic events":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probabilistic reasoning in the description logic alcp with the principle of maximum entropy full version")
  Member "random worlds and maximum entropy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reasoning under the principle of maximum entropy for modal logics k45 kd45 and s5")

Question: Please tell me which class the source paper 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)