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: "gene expression programming a new adaptive algorithm for solving problems"
  Abstract: Gene expression programming, a genotype/phenotype genetic algorithm (linear and ramified), is presented here for the first time as a new technique for the creation of computer programs. Gene expression programming uses character linear chromosomes composed of genes structurally organized in a head and a tail. The chromosomes function as a genome and are subjected to modification by means of mutation, transposition, root transposition, gene transposition, gene recombination, and one- and two-point recombination. The chromosomes encode expression trees which are the object of selection. The creation of these separate entities (genome and expression tree) with distinct functions allows the algorithm to perform with high efficiency that greatly surpasses existing adaptive techniques. The suite of problems chosen to illustrate the power and versatility of gene expression programming includes symbolic regression, sequence induction with and without constant creation, block stacking, cellular automata rules for the density-classification problem, and two problems of boolean concept learning: the 11-multiplexer and the GP rule problem.

Connected through hyperedge HE-1 (induced by source paper "2019 evolutionary algorithms review"):
  with members:
    - "guided evolutionary strategies escaping the curse of dimensionality in random search"
    - "evolving simple programs for playing atari games"
    - "markov brains a technical introduction"
    - "deep neuroevolution genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "a novel continuous representation of genetic programmings using recurrent neural networks for symbolic regression"):
  with members:
    - "where are we now a large benchmark study of recent symbolic regression methods"
    - "text generation based on generative adversarial nets with latent variable"
    - "c rnn gan continuous recurrent neural networks with adversarial training"
    - "generating sentences from a continuous space"

Connected through hyperedge HE-3 (induced by source paper "a self adaptive network protection system"):
  with members:
    - "current studies on intrusion detection system genetic algorithm and fuzzy logic"
    - "current studies on intrusion detection system genetic algorithm and fuzzy logic"
    - "immune system approaches to intrusion detection a review"

Connected through hyperedge HE-4 (induced by source paper "a brief review of nature inspired algorithms for optimization"):
  with members:
    - "circle detection using electro magnetism optimization"
    - "a comprehensive review of firefly algorithms"
    - "multi objective flower algorithm for optimization"
    - "distributed graph coloring an approach based on the calling behavior of japanese tree frogs"

Connected through hyperedge HE-5 (induced by source paper "on mobile dna in artificial regulatory networks evolving functional and structural dynamism"):
  with members:
    - "classification of random boolean networks"

Connected through hyperedge HE-6 (induced by source paper "on natural genetic engineering structural dynamism in random boolean networks"):
  with members:
    - "classification of random boolean networks"

Connected through hyperedge HE-7 (induced by source paper "degenerate neutrality creates evolvable fitness landscapes"):
  with members:
    - "adaptation and self organization in evolutionary algorithms"

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)