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 "autonomous robots and the sp theory of intelligence"):
  Abstract: This paper is about how the SP theory of intelligence and its realization in the SP machine (both outlined in this paper) may help in the design of the brains of autonomous robots, meaning robots that do not depend on external intelligence or power supplies, are mobile, and have human-like versatility and adaptability in intelligence. This paper addresses three main problems: 1) how to increase the computational and energy efficiency of computers and to reduce their size and weight; 2) how to achieve human-like versatility in intelligence; and 3) likewise for human-like adaptability in intelligence. Regarding the first problem, the SP system has the potential for substantial gains in computational efficiency, with corresponding cuts in energy consumption and the bulkiness of computers: 1) by reducing the size of data to be processed; 2) by exploiting statistical information that the system gathers as an integral part of how it works; and 3) via a new version of Donald Hebb's concept of a cell assembly. Toward human-like versatility in intelligence, the SP system has strengths in unsupervised learning, natural language processing, pattern recognition, information retrieval, several kinds of reasoning, planning, problem solving, and more, with seamless integration among structures and functions. The SP system's strengths in unsupervised learning and other aspects of intelligence may help in achieving human-like adaptability in intelligence via: 1) one-trial learning; 2) learning of natural language; 3) learning to see; 4) building 3-D models of objects and of a robot's surroundings; 5) learning regularities in the workings of a robot and in the robot's environment; 6) exploration and play; 7) learning major skills; and 8) learning via demonstration. Also discussed are how the SP system may process parallel streams of information, generalization of knowledge, correction of over-generalizations, learning from dirty data, how to cut the cost of learning, and reinforcements and motivations.

Includes members:
  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-1 (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-2 (induced by source paper "introduction to the sp theory of intelligence")
  Member "the sp theory of intelligence benefits and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "introduction to the sp theory of intelligence")
  Member "the sp theory of intelligence an overview":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "introduction to the sp theory of intelligence")
  Member "towards an intelligent database system founded on the sp theory of computing and cognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "introduction to the sp theory of intelligence")
  Member "medical diagnosis as pattern recognition in a framework of information compression by multiple alignment unification and search":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "introduction to the sp theory of intelligence")

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)