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 "turning 30 new ideas in inductive logic programming"):
  Abstract: Common criticisms of state-of-the-art machine learning include poor generalisation, a lack of interpretability, and a need for large amounts of training data. We survey recent work in inductive logic programming (ILP), a form of machine learning that induces logic programs from data, which has shown promise at addressing these limitations. We focus on new methods for learning recursive programs that generalise from few examples, a shift from using hand-crafted background knowledge to \emph{learning} background knowledge, and the use of different technologies, notably answer set programming and neural networks. As ILP approaches 30, we also discuss directions for future research.

Includes members:
  Member "learning higher order logic programs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "on the measure of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "neural logic machines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "relational neural machines")
  Member "logical reduction of metarules":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "forgetting to learn logic programs")
  Member "forgetting to learn logic programs":
    also connected through other hyperedges:
      (none)
  Member "playgol learning programs through play":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "from statistical relational to neuro symbolic artificial intelligence")
  Member "synthesizing datalog programs using numerical relaxation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "from statistical relational to neuro symbolic artificial intelligence")
  Member "learning relational representations with auto encoding logic programs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relational neural machines")

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)