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: "DNA: A New ASOCS Model With Improved Implementation Potential"
  Abstract: A new class of highspeed, self-adaptive, massively parallel computing models called ASOCS (Adaptive Self-Organizing Concurrent Systems) has been proposed. Current analysis suggests that there may be problems implementing ASOCS models in VLSI using the hierarchical network structures originally proposed. The problems are not inherent in the models, but rather in the technology used to implement them. This has led to the development of a new ASOCS model called DNA (Discriminant-Node ASOCS) that does not depend on a hierarchical node structure for success. Three areas of the DNA model are briefly discussed in this paper: DNA's flexible nodes, how DNA overcomes problems other models have allocating unused nodes, and how DNA operates during processing and learning.

Connected through hyperedge HE-1 (induced by source paper "Models of Parallel Adaptive Logic"):
  with members:
    - "Neural Network Applicability: Classifying the Problem Space"
    - "ASOCS: A Multilayered Connectionist Network with Guaranteed Learning of Arbitrary Mappings"
    - "Digital Neural Networks"

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: Neural_Networks