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: "Soft Computing: the Convergence of Emerging Reasoning Technologies"
  Abstract: The term Soft Computing (SC) represents the combination of emerging problem-solving technologies such as Fuzzy Logic (FL), Probabilistic Reasoning (PR), Neural Networks (NNs), and Genetic Algorithms (GAs). Each of these technologies provide us with complementary reasoning and searching methods to solve complex, real-world problems. After a brief description of each of these technologies, we will analyze some of their most useful combinations, such as the use of FL to control GAs and NNs parameters; the application of GAs to evolve NNs (topologies or weights) or to tune FL controllers; and the implementation of FL controllers as NNs tuned by backpropagation-type algorithms.

Connected through hyperedge HE-1 (induced by source paper "Evolution of the Topology and the Weights of Neural Networks using Genetic Programming with a"):
  with members:
    - "A Hypothesis-driven Constructive Induction Approach to Expanding Neural Networks"
    - "Genetic Encoding Strategies for Neural Networks"

Connected through hyperedge HE-2 (induced by source paper "Dynamic Control of Genetic Algorithms using Fuzzy Logic Techniques"):
  with members:
    - "Empirical studies of the genetic algorithm with non-coding segments"
    - "Dynamic Parameter Encoding for Genetic Algorithms"
    - "Basic PSugal an extension package for the development of Distributed Genetic Algorithms"

Connected through hyperedge HE-3 (induced by source paper "Genetic Algorithms for Automated Tuning of Fuzzy Controllers: A Transportation Application"):
  with members:
    (none)

Connected through hyperedge HE-4 (induced by source paper "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"):
  with members:
    - "Topography And Ocular Dominance: A Model Exploring Positive Correlations"
    - "Constrained Optimization for Neural Map Formation: A Unifying Framework for Weight Growth and Normalization"
    - "Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex"
    - "Generative Models for Discovering Sparse Distributed Representations"
    - "SCRIPT RECOGNITION WITH HIERARCHICAL FEATURE MAPS"
    - "SELF-ORGANIZING PROCESS BASED ON LATERAL INHIBITION AND SYNAPTIC RESOURCE REDISTRIBUTION"
    - "IEEE Learning the Semantic Similarity of Reusable Software Components"
    - "Self-Organization and Segmentation in a Laterally Connected Orientation Map of Spiking Neurons"

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