human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Investigating the role of diploidy in simulated populations of evolving individuals"):
  Abstract: In most work applying genetic algorithms to populations of neural networks there is no real distinction between genotype and phenotype. In nature both the information contained in the genotype and the mapping of the genetic information into the phenotype are usually much more complex. The genotypes of many organisms exhibit diploidy, i.e., they include two copies of each gene: if the two copies are not identical in their sequences and therefore have a functional difference in their products (usually proteins), the expressed phenotypic feature is termed the dominant one, the other one recessive (not expressed). In this paper we review the literature on the use of diploidy and dominance operators in genetic algorithms; we present the new results we obtained with our own simulations in changing environments; finally, we discuss some results of our simulations that parallel biological findings.

Includes members:
  Member "Two is better than one: A diploid genotype for neural networks":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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