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 "Constraining of Weights using Regularities"):
  Abstract: In this paper we study how global optimization methods (like genetic algorithms) can be used to train neural networks. We introduce the notion of regularity, for studying properties of the error function that expand the search space in an artificial way. Regularities are used to generate constraints on the weights of the network. In order to find a satisfiable set of constraints we use a constraint logic programming system. Then the training of the network becomes a constrained optimization problem. We also relate the notion of regularity to so-called network transformations.

Includes members:
  Member "Evolutionary Training of CLP-Constrained Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Forward-Tracking: A Technique for Searching Beyond Failure")
  Member "Forward-Tracking: A Technique for Searching Beyond Failure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Evolutionary Training of CLP-Constrained 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