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 "probabilistic reasoning with answer sets"):
  Abstract: This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give several non-trivial examples and illustrate the use of P-log for knowledge representation and updating of knowledge. We argue that our approach to updates is more appealing than existing approaches. We give sufficiency conditions for the coherency of P-log programs and show that Bayes nets can be easily mapped to coherent P-log programs.

Includes members:
  Member "loglinear models for first order probabilistic reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relational dynamic bayesian networks")
  Member "clp bn constraint logic programming for probabilistic knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "probabilistic logic neural networks for reasoning")
  Member "the dlv system for knowledge representation and reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the seventh answer set programming competition design and results")
  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 "weight constraints as nested expressions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "strong equivalence and program s structure in arguing essential equivalence between logic programs")
  Member "bayesian logic programs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "anytime exact belief propagation")

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)