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 "natural scene statistics mediate the perception of image complexity"):
  Abstract: Humans are sensitive to complexity and regularity in patterns (Falk & Konold, 1997; Yamada, Kawabe, & Miyazaki, 2013). The subjective perception of pattern complexity is correlated to algorithmic (or Kolmogorov-Chaitin) complexity as defined in computer science (Li & Vitanyi, 2008), but also to the frequency of naturally occurring patterns (Hsu, Griffiths, & Schreiber, 2010). However, the possible mediational role of natural frequencies in the perception of algorithmic complexity remains unclear. Here we reanalyze Hsu et al. (2010) through a mediational analysis, and complement their results in a new experiment. We conclude that human perception of complexity seems partly shaped by natural scenes statistics, thereby establishing a link between the perception of complexity and the effect of natural scene statistics.

Includes members:
  Member "algorithmic complexity for short binary strings applied to psychology a primer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "slime mould the fundamental mechanisms of cognition")
  Member "correspondence and independence of numerical evaluations of algorithmic information measures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data dimension reduction and network sparsification based on minimal algorithmic information loss")
  Member "calculating kolmogorov complexity from the output frequency distributions of small turing machines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ab initio algorithmic causal deconvolution of intertwined programs and networks by generative mechanism")
  Member "image characterization and classification by physical complexity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unpredictability and computational irreducibility")

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)