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 "Culling Teaching -1 Culling and Teaching in Neuro-evolution"):
  Abstract: The evolving population of neural nets contains information not only in terms of genes, but also in the collection of behaviors of the population members. Such information can be thought of as a kind of culture of the population. Two ways of exploiting that culture are explored in this paper: (1) Culling overlarge litters: Generate a large number of offspring with different crossovers, quickly evaluate them by comparing their performance to the population, and throw away those that appear poor. (2) Teaching: Use backpropagation to train offspring toward the performance of the population. Both techniques result in faster, more effective neuro-evolution, and they can be effectively combined, as is demonstrated on the inverted pendulum problem. Additional methods of cultural exploitation are possible and will be studied in future work. These results suggest that cultural exploitation is a powerful idea that allows leveraging several aspects of the genetic algorithm.

Includes members:
  Member "References elements that can solve difficult learning control problems. on Simulation of Adaptive Behavior, pages":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Complexity Compression and Evolution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Evolving Compact Solutions in Genetic Programming: A Case Study")
  Member "Genes, Phenes and the Baldwin Effect: Learning and Evolution in a Simulated Population":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Landscapes, Learning Costs and Genetic Assimilation.")
  Member "Cellular Encoding Applied to Neurocontrol":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks")

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