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 "Orgy in the Computer: Multi-Parent Reproduction in Genetic Algorithms"):
  Abstract: In this paper we investigate the phenomenon of multi-parent reproduction, i.e. we study recombination mechanisms where an arbitrary n &gt; 1 number of parents participate in creating children. In particular, we discuss scanning crossover that generalizes the standard uniform crossover and diagonal crossover that generalizes 1-point crossover, and study the effects of different number of parents on the GA behavior. We conduct experiments on tough function optimization problems and observe that by multi-parent operators the performance of GAs can be enhanced significantly. We also give a theoretical foundation by showing how these operators work on distributions.

Includes members:
  Member "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley.":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Evolving Graphs and Networks with Edge Encoding: Preliminary Report")
  Member "Genetic algorithms with multi-parent recombination":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Multi-parent's niche: n-ary crossovers on NK-landscapes")
  Member "A Cooperative Coevolutionary Approach to Function Optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Genetic Algorithms as Multi-Coordinators in Large-Scale Optimization")
  Member "Multi-parent Recombination":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Adapting Crossover in Evolutionary Algorithms")
  Member "Graph Coloring with Adaptive Evolutionary Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Solving 3-SAT by GAs Adapting Constraint Weights")

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