human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Duplication of Coding Segments in Genetic Programming"
  Abstract: Research into the utility of non-coding segments, or introns, in genetic-based encodings has shown that they expedite the evolution of solutions in domains by protecting building blocks against destructive crossover. We consider a genetic programming system where non-coding segments can be removed, and the resultant chromosomes returned into the population. This parsimonious repair leads to premature convergence, since as we remove the naturally occurring non-coding segments, we strip away their protective backup feature. We then duplicate the coding segments in the repaired chromosomes, and place the modified chromosomes into the population. The duplication method significantly improves the learning rate in the domain we have considered. We also show that this method can be applied to other domains.

Connected through hyperedge HE-1 (induced by source paper "A Comparison of Random Search versus Genetic Programming as Engines for Collective Adaptation"):
  with members:
    - "Strongly Typed Genetic Programming"
    - "Type Inheritance in Strongly Typed Genetic Programming"

Connected through hyperedge HE-2 (induced by source paper "A comparison of the fixed and floating building block representation in the genetic algorithm"):
  with members:
    - "The Royal Road for Genetic Algorithms: Fitness Landscapes and GA Performance"
    - "Empirical studies of the genetic algorithm with non-coding segments"
    - "A Survey of Intron Research in Genetics"
    - "Testing the Robustness of the Genetic Algorithm on the Floating Building Block Representation."

Connected through hyperedge HE-3 (induced by source paper "Entailment for Specification Refinement"):
  with members:
    - "Strongly Typed Genetic Programming"
    - "Type Inheritance in Strongly Typed Genetic Programming"
    - "Induction and Recapitulation of Deep Musical Structure"

Connected through hyperedge HE-4 (induced by source paper "A Survey of Intron Research in Genetics"):
  with members:
    - "Empirical studies of the genetic algorithm with non-coding segments"
    - "Complexity Compression and Evolution"
    - "A comparison of the fixed and floating building block representation in the genetic algorithm"
    - "Evolving Turing-Complete Programs for a Register Machine with Self-modifying Code"

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Genetic_Algorithms