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: "ADAPTIVE LOOK-AHEAD PLANNING problem of finding good initial plans is solved by the use of"
  Abstract: We present a new adaptive connectionist planning method. By interaction with an environment a world model is progressively constructed using the backpropagation learning algorithm. The planner constructs a look-ahead plan by iteratively using this model to predict future reinforcements. Future reinforcement is maximized to derive suboptimal plans, thus determining good actions directly from the knowledge of the model network (strategic level). This is done by gradient descent in action space.

Connected through hyperedge HE-1 (induced by source paper "INVERSION IN TIME"):
  with members:
    (none)

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