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: "Predictive Robot Control with Neural Networks"
  Abstract: Neural controllers are able to position the hand-held camera of the (3DOF) anthropomorphic OSCAR-robot manipulator above an object which is arbitrary placed on a table. The desired camera-joint mapping is approximated by feedforward neural networks. However, if the object is moving, the manipulator lags behind because of the required time to preprocess the visual information and to move the manipulator. Through the use of time derivatives of the position of the object and of the manipulator, the controller can inherently predict the next position of the object. In this paper several `predictive' controllers are proposed, and successfully applied to track a moving object.

Connected through hyperedge HE-1 (induced by source paper "Constructive Training Methods for Feedforward Neural Networks with Binary Weights"):
  with members:
    - "Combining Linear Discriminant Functions with Neural Networks for Supervised Learning"
    - "Approximation with neural networks: Between local and global approximation"
    - "Orthogonal incremental learning of a feedforward network"
    - "Visual Tracking of Moving Objects using a Neural Network Controller"
    - "The locally linear Nested Network for robot manipulation"
    - "Maximizing the Robustness of a Linear Threshold Classifier with Discrete Weights"
    - "Two Constructive Methods for Designing Compact Feedforward Networks of Threshold Units"

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