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 "the sp theory of intelligence its distinctive features and advantages"):
  Abstract: This paper aims to highlight distinctive features of the "SP theory of intelligence" and its apparent advantages compared with some AI-related alternatives. The theory is outlined in an appendix. The distinctive features and advantages are summarised: simplification and integration of observations and concepts, and of structures and processes in computing systems; the SP theory is itself a theory of computing; a central role for information compression via the matching and unification of patterns, and for multiple alignment; transparency in the representation and processing of knowledge; the discovery of 'natural' structures via information compression (DONSVIC); interpretation of aspects of mathematics; interpretation of phenomena in human perception and cognition; realisation of abstract concepts in terms of neurons and their inter-connections ("SP-neural"). Distinctive features and advantages of the SP system compared with alternatives in: minimum length encoding and related concepts; deep learning in neural networks; universal search; Bayesian networks and other models for AI; analysis and production of natural language; learning natural language; exact and inexact reasoning; representation and processing of diverse forms of knowledge; IBM's Watson; problems associated with big data, and in the development of intelligence in autonomous robots. In conclusion, a major strength of SP system is that it can provide a firm foundation for the long-term development of AI and, at the same time, it may deliver some benefits and applications on relatively short timescales. It is envisaged that a high-parallel, open-source version of the SP machine will be created, hosted on an existing high-performance computer and derived from the existing SP computer model. This will be a means for researchers everywhere to explore what can be done with the system, and to create new versions of it.

Includes members:
  Member "deep learning in neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "π nets deep polynomial neural networks")
  Member "text understanding from scratch":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "filter grafting for deep neural networks")
  Member "sketch a net that beats humans":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning robust representations via multi view information bottleneck")
  Member "neural turing machines":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mast a memory augmented self supervised tracker")
  Member "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "introduction to the sp theory of intelligence")
  Member "big data 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 "autonomous robots and the sp theory of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "introduction to the sp theory of intelligence")
  Member "intriguing properties of neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adversarial ranking attack and defense")

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)