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 "Program Search with a Hierarchical Variable Length Representation: Genetic Programming, Simulated Annealing and Hill Climbing"):
  Abstract: This paper presents a comparison of Genetic Programming(GP) with Simulated Annealing (SA) and Stochastic Iterated Hill Climbing (SIHC) based on a suite of program discovery problems which have been previously tackled only with GP. All three search algorithms employ the hierarchical variable length representation for programs brought into recent prominence with the GP paradigm [8]. We feel it is not intuitively obvious that mutation-based adaptive search can handle program discovery yet, to date, for each GP problem we have tried, SA or SIHC also work.

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 "The Troubling Aspects of a Building Block Hypothesis for Genetic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Genetic Programming Exploratory Power and the Discovery of Functions")
  Member "Investigating the Generality of Automatically Defined Functions":
    also connected through other hyperedges:
      (none)
  Member "Hybridized Crossover-Based Search Techniques for Program Discovery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "An Adverse Interaction between the Crossover Operator and a Restriction on Tree Depth of Crossover")

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