human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the sp theory of intelligence distinctive features and advantages"
  Abstract: This paper aims to highlight distinctive features of the SP theory of intelligence, realized in the SP computer model, and its apparent advantages compared with some AI-related alternatives. Perhaps most importantly, the theory simplifies and integrates observations and concepts in AI-related areas, and has potential to simplify and integrate of structures and processes in computing systems. Unlike most other AI-related theories, the SP theory is itself a theory of computing, which can be the basis for new architectures for computers. Fundamental in the theory is information compression via the matching and unification of patterns and, more specifically, via a concept of multiple alignment. The theory promotes transparency in the representation and processing of knowledge, and unsupervised learning of natural structures via information compression. It provides an interpretation of aspects of mathematics and an interpretation of phenomena in human perception and cognition. concepts in the theory may be realized in terms of neurons and their inter-connections (SP-neural). These features and advantages of the SP system are discussed in relation to AI-related alternatives: the concept of minimum length encoding and related concepts, how computational and energy efficiency in computing may be achieved, deep learning in neural networks, unified theories of cognition and related research, universal search, Bayesian networks and some other models for AI, IBM’s Watson, solving problems associated with big data and in the development of intelligence in autonomous robots, pattern recognition and vision, the learning and processing of natural language, exact and inexact forms of reasoning, representation and processing of diverse forms of knowledge, and software engineering. In conclusion, the SP system can provide a firm foundation for the long-term development of AI and related areas, and at the same time, it may deliver useful results on relatively short timescales.

Connected through hyperedge HE-1 (induced by source paper "introduction to the sp theory of intelligence"):
  with members:
    - "solutions to problems with deep learning"
    - "software engineering and the sp theory of intelligence"
    - "information compression multiple alignment and the representation and processing of knowledge in the brain"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "deep learning in neural networks"
    - "the sp theory of intelligence its distinctive features and advantages"
    - "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision"
    - "big data and the sp theory of intelligence"

Connected through hyperedge HE-2 (induced by source paper "interpreting winograd schemas via the sp theory of intelligence and its realisation in the sp computer model"):
  with members:
    - "introduction to the sp theory of intelligence"
    - "mathematics as information compression via the matching and unification of patterns"
    - "solutions to problems with deep learning"
    - "software engineering and the sp theory of intelligence"
    - "information compression multiple alignment and the representation and processing of knowledge in the brain"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "deep learning in neural networks"
    - "the sp theory of intelligence its distinctive features and advantages"

Connected through hyperedge HE-3 (induced by source paper "solutions to problems with deep learning"):
  with members:
    - "impala scalable distributed deep rl with importance weighted actor learner architectures"
    - "deep learning a critical appraisal"
    - "deep reinforcement learning that matters"
    - "overcoming catastrophic forgetting in neural networks"
    - "information compression multiple alignment and the representation and processing of knowledge in the brain"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "deep learning in neural networks"
    - "the sp theory of intelligence its distinctive features and advantages"

Connected through hyperedge HE-4 (induced by source paper "dual approach for object tracking based on optical flow and swarm intelligence"):
  with members:
    - "deep learning a critical appraisal"
    - "solutions to problems with deep learning"
    - "crest convolutional residual learning for visual tracking"
    - "long term visual object tracking benchmark"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "learning multi domain convolutional neural networks for visual tracking"
    - "the sp theory of intelligence its distinctive features and advantages"
    - "on the fly learning in a perpetual learning machine"

Connected through hyperedge HE-5 (induced by source paper "mathematics as information compression via the matching and unification of patterns"):
  with members:
    - "introduction to the sp theory of intelligence"
    - "development of the sp machine"
    - "software engineering and the sp theory of intelligence"
    - "information compression multiple alignment and the representation and processing of knowledge in the brain"
    - "the sp theory of intelligence its distinctive features and advantages"
    - "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision"
    - "big data and the sp theory of intelligence"
    - "autonomous robots and the sp theory of intelligence"

Connected through hyperedge HE-6 (induced by source paper "development of the sp machine"):
  with members:
    - "introduction to the sp theory of intelligence"
    - "solutions to problems with deep learning"
    - "software engineering and the sp theory of intelligence"
    - "overcoming catastrophic forgetting in neural networks"
    - "information compression multiple alignment and the representation and processing of knowledge in the brain"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "deep learning in neural networks"
    - "the sp theory of intelligence its distinctive features and advantages"

Connected through hyperedge HE-7 (induced by source paper "software engineering and the sp theory of intelligence"):
  with members:
    - "introduction to the sp theory of intelligence"
    - "overcoming catastrophic forgetting in neural networks"
    - "commonsense reasoning commonsense knowledge and the sp theory of intelligence"
    - "the sp theory of intelligence its distinctive features and advantages"
    - "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision"
    - "big data and the sp theory of intelligence"
    - "autonomous robots and the sp theory of intelligence"
    - "the sp theory of intelligence benefits and applications"

Connected through hyperedge HE-8 (induced by source paper "information compression multiple alignment and the representation and processing of knowledge in the brain"):
  with members:
    - "deep learning in neural networks"
    - "proposal for the creation of a research facility for the development of the sp machine"
    - "the sp theory of intelligence its distinctive features and advantages"
    - "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision"
    - "big data and the sp theory of intelligence"
    - "autonomous robots and the sp theory of intelligence"
    - "the sp theory of intelligence benefits and applications"
    - "the sp theory of intelligence an overview"

Question: Please tell me which class the center node 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)