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: "two dimensional kolmogorov complexity and validation of the coding theorem method by compressibility"
  Abstract: We propose a measure based upon the fundamental theoretical concept in algorithmic information theory that provides a natural approach to the problem of evaluating $n$-dimensional complexity by using an $n$-dimensional deterministic Turing machine. The technique is interesting because it provides a natural algorithmic process for symmetry breaking generating complex $n$-dimensional structures from perfectly symmetric and fully deterministic computational rules producing a distribution of patterns as described by algorithmic probability. Algorithmic probability also elegantly connects the frequency of occurrence of a pattern with its algorithmic complexity, hence effectively providing estimations to the complexity of the generated patterns. Experiments to validate estimations of algorithmic complexity based on these concepts are presented, showing that the measure is stable in the face of some changes in computational formalism and that results are in agreement with the results obtained using lossless compression algorithms when both methods overlap in their range of applicability. We then use the output frequency of the set of 2-dimensional Turing machines to classify the algorithmic complexity of the space-time evolutions of Elementary Cellular Automata.

Connected through hyperedge HE-1 (induced by source paper "ab initio algorithmic causal deconvolution of intertwined programs and networks by generative mechanism"):
  with members:
    - "parameter free network sparsification and data reduction by minimal algorithmic information loss"
    - "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability"
    - "low algorithmic complexity entropy deceiving graphs"
    - "algorithmically probable mutations reproduce aspects of evolution such as convergence rate genetic memory and modularity"
    - "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity"
    - "on the necessity of complexity"
    - "nonnegative decomposition of multivariate information"
    - "the generalized universal law of generalization"

Connected through hyperedge HE-2 (induced by source paper "algorithmically probable mutations reproduce aspects of evolution such as convergence rate genetic memory and modularity"):
  with members:
    - "coding theorem like behaviour and emergence of the universal distribution from resource bounded algorithmic probability"
    - "low algorithmic complexity entropy deceiving graphs"
    - "undecidability and irreducibility conditions for open ended evolution and emergence"
    - "a decomposition method for global evaluation of shannon entropy and local estimations of algorithmic complexity"
    - "the limits of decidable states on open ended evolution and emergence"
    - "a computable measure of algorithmic probability by finite approximations with an application to integer sequences"
    - "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"

Connected through hyperedge HE-3 (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"
    - "natural scene statistics mediate the perception of image complexity"
    - "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"
    - "on the algorithmic nature of the world"

Connected through hyperedge HE-4 (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"
    - "natural scene statistics mediate the perception of image complexity"
    - "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"

Connected through hyperedge HE-5 (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"
    - "natural scene statistics mediate the perception of image complexity"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "numerical investigation of graph spectra and information interpretability of eigenvalues"):
  with members:
    - "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"
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"
    - "search space contraction in canonical labeling of graphs"

Connected through hyperedge HE-7 (induced by source paper "correlation of automorphism group size and topological properties with program size complexity evaluations of graphs and complex networks"):
  with members:
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "conflict anticipation in the search for graph automorphisms"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "numerical evaluation of algorithmic complexity for short strings a glance into the innermost structure of randomness"
    - "on the algorithmic nature of the world"
    - "on the kolmogorov chaitin complexity for short sequences"
    - "complexity of networks"

Connected through hyperedge HE-8 (induced by source paper "algorithmic complexity for psychology a user friendly implementation of the coding theorem method"):
  with members:
    - "algorithmic complexity for short binary strings applied to psychology a primer"
    - "natural scene statistics mediate the perception of image complexity"
    - "correspondence and independence of numerical evaluations of algorithmic information measures"
    - "calculating kolmogorov complexity from the output frequency distributions of small turing machines"
    - "on the algorithmic nature of the world"
    - "the google similarity distance"

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.CC(Computational Complexity)