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 "rudas synthetic datasets for rule learning and evaluation tools"):
  Abstract: Logical rules are a popular knowledge representation language in many domains, representing background knowledge and encoding information that can be derived from given facts in a compact form. However, rule formulation is a complex process that requires deep domain expertise, and is further challenged by today's often large, heterogeneous, and incomplete knowledge graphs. Several approaches for learning rules automatically, given a set of input example facts, have been proposed over time, including, more recently, neural systems. Yet, the area is missing adequate datasets and evaluation approaches: existing datasets often resemble toy examples that neither cover the various kinds of dependencies between rules nor allow for testing scalability. We present a tool for generating different kinds of datasets and for evaluating rule learning systems.

Includes members:
  Member "neural logic machines":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relational neural machines")
  Member "differentiable reasoning on large knowledge bases and natural language":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "transformers as soft reasoners over language")
  Member "deepproblog neural probabilistic logic programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "logical rule induction and theory learning using neural theorem proving":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural logic machines")
  Member "towards neural theorem proving at scale":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transformers as soft reasoners over language")
  Member "learning explanatory rules from noisy data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "differentiable learning of logical rules for knowledge base reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "rdf2rules learning rules from rdf knowledge bases by mining frequent predicate cycles":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "iteratively learning embeddings and rules for knowledge graph reasoning")

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)