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: "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.

Connected through hyperedge HE-1 (induced by source paper "paths to unconventional computing causality in complexity"):
  with members:
    - "algorithmic data analytics small data matters and correlation versus causation"
    - "asymptotic intrinsic universality and natural reprogrammability by behavioural emulation"
    - "causality information and biological computation an algorithmic software approach to life disease and the immune system"
    - "cross boundary behavioural reprogrammability of cellular automata from emulation networks"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "what is nature like computation a behavioural approach and a notion of programmability"
    - "a behavioural foundation for natural computing and a programmability test"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"

Connected through hyperedge HE-2 (induced by source paper "algorithmic data analytics small data matters and correlation versus causation"):
  with members:
    - "low algorithmic complexity entropy deceiving graphs"
    - "numerical investigation of graph spectra and information interpretability of eigenvalues"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"
    - "on the algorithmic nature of the world"

Connected through hyperedge HE-3 (induced by source paper "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability"):
  with members:
    - "computing by nowhere increasing complexity"
    - "algorithmically probable mutations reproduce aspects of evolution such as convergence rate genetic memory and modularity"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "kolmogorov complexity and solovay functions"
    - "towards a stable definition of kolmogorov chaitin complexity"
    - "optimal ordered problem solver"

Connected through hyperedge HE-4 (induced by source paper "slime mould the fundamental mechanisms of cognition"):
  with members:
    - "low algorithmic complexity entropy deceiving graphs"
    - "algorithmically probable mutations reproduce aspects of evolution such as convergence rate genetic memory and modularity"
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "on creativity of slime mould"
    - "physarum machine implementation of a kolmogorov uspensky machine on a biological substrate"

Connected through hyperedge HE-5 (induced by source paper "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity"):
  with members:
    - "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability"
    - "low algorithmic complexity entropy deceiving graphs"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "on the kolmogorov chaitin complexity for short sequences"
    - "most programs stop quickly or never halt"

Connected through hyperedge HE-6 (induced by source paper "the information theoretic and algorithmic approach to human animal and artificial cognition"):
  with members:
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "is consciousness computable quantifying integrated information using algorithmic information theory"
    - "what is nature like computation a behavioural approach and a notion of programmability"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "algorithmic simplicity and relevance"
    - "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"

Connected through hyperedge HE-7 (induced by source paper "a computable measure of algorithmic probability by finite approximations"):
  with members:
    - "algorithmic data analytics small data matters and correlation versus causation"
    - "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity"
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"

Connected through hyperedge HE-8 (induced by source paper "a computable measure of algorithmic probability by finite approximations with an application to integer sequences"):
  with members:
    - "low algorithmic complexity entropy deceiving graphs"
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"
    - "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"

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)