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 "interpreting winograd schemas via the sp theory of intelligence and its realisation in the sp computer model"):
  Abstract: In 'Winograd Schema' (WS) sentences like "The city councilmen refused the demonstrators a permit because they feared violence" and "The city councilmen refused the demonstrators a permit because they advocated revolution", it is easy for adults to understand what "they" refers to but can be difficult for AI systems. This paper describes how the SP System -- outlined in an appendix -- may solve this kind of problem of interpretation. The central idea is that a knowledge of discontinuous associations amongst linguistic features, and an ability to recognise such patterns of associations, provides a robust means of determining what a pronoun like "they" refers to. For any AI system to solve this kind of problem, it needs appropriate knowledge of relevant syntax and semantics which, ideally, it should learn for itself. Although the SP System has some strengths in unsupervised learning, its capabilities in this area are not yet good enough to learn the kind of knowledge needed to interpret WS examples, so it must be supplied with such knowledge at the outset. However, its existing strengths in unsupervised learning suggest that it has potential to learn the kind of knowledge needed for the interpretation of WS examples. In particular, it has potential to learn the kind of discontinuous association of linguistic features mentioned earlier.

Includes members:
  Member "introduction to the sp theory of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mathematics as information compression via the matching and unification of patterns")
  Member "mathematics as information compression via the matching and unification of patterns":
    also connected through other hyperedges:
      (none)
  Member "solutions to problems with deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "introduction to the sp theory of intelligence")
  Member "software engineering and the sp theory of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "introduction to the sp theory of intelligence")
  Member "information compression multiple alignment and the representation and processing of knowledge in the brain":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "introduction to the sp theory of intelligence")
  Member "the sp theory of intelligence distinctive features and advantages":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "introduction to the sp theory of intelligence")
  Member "commonsense reasoning commonsense knowledge and the sp theory of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "introduction to the sp theory of intelligence")
  Member "deep learning in neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "π nets deep polynomial neural networks")

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)