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: "Investigating the Generality of Automatically Defined Functions"
  Abstract: This paper studies how well the combination of simulated annealing and ADFs solves genetic programming (GP) style program discovery problems. On a suite composed of the even-k-parity problems for k = 3,4,5, it analyses the performance of simulated annealing with ADFs as compared to not using ADFs. In contrast to GP results on this suite, when simulated annealing is run with ADFs, as problem size increases, the advantage to using them over a standard GP program representation is marginal. When the performance of simulated annealing is compared to GP with both algorithm using ADFs on the even-3-parity problem GP is advantageous, on the even-4-parity problem SA and GP are equal, and on the even-5-parity problem SA is advantageous.

Connected through hyperedge HE-1 (induced by source paper "Program Search with a Hierarchical Variable Length Representation: Genetic Programming, Simulated Annealing and Hill Climbing"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "The Troubling Aspects of a Building Block Hypothesis for Genetic Programming"
    - "Hybridized Crossover-Based Search Techniques for Program Discovery"

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