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 "ASOCS: A Multilayered Connectionist Network with Guaranteed Learning of Arbitrary Mappings"):
  Abstract: This paper reviews features of a new class of multilayer connectionist architectures known as ASOCS (Adaptive Self-Organizing Concurrent Systems). ASOCS is similar to most decision-making neural network models in that it attempts to learn an adaptive set of arbitrary vector mappings. However, it differs dramatically in its mechanisms. ASOCS is based on networks of adaptive digital elements which self-modify using local information. Function specification is entered incrementally by use of rules, rather than complete input-output vectors, such that a processing network is able to extract critical features from a large environment and give output in a parallel fashion. Learning also uses parallelism and self-organization such that a new rule is completely learned in time linear with the depth of the network. The model guarantees learning of any arbitrary mapping of boolean input-output vectors. The model is also stable in that learning does not erase any previously learned mappings except those explicitly contradicted.

Includes members:
  Member "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Models of Parallel Adaptive Logic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "DNA: A New ASOCS Model With Improved Implementation Potential")

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: Neural_Networks