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: "Path-integral evolution of chaos embedded in noise: Duffing neocortical analog"
  Abstract: A two dimensional time-dependent Duffing oscillator model of macroscopic neocortex exhibits chaos for some ranges of parameters. We embed this model in moderate noise, typical of the context presented in real neocortex, using PATHINT, a non-Monte-Carlo path-integral algorithm that is particularly adept in handling nonlinear Fokker-Planck systems. This approach shows promise to investigate whether chaos in neocortex, as predicted by such models, can survive in noisy contexts.

Connected through hyperedge HE-1 (induced by source paper "Statistical Mechanics of Nonlinear Nonequilibrium Financial Markets: Applications to Optimized Trading"):
  with members:
    - "Noisy Time Series Prediction using Symbolic Representation and Recurrent Neural Network Grammatical Inference"
    - "Volatility of Volatility of Financial Markets"
    - "%A L. Ingber %T Adaptive simulated annealing (ASA): Lessons learned %J Control and Cybernetics Annealing"
    - "STATISTICAL MECHANICS OF COMBAT WITH HUMAN FACTORS"
    - "Statistical mechanics of neocortical interactions: Training and testing canonical momenta indicators of EEG"
    - "NONLINEAR NONEQUILIBRIUM NONQUANTUM NONCHAOTIC STATISTICAL MECHANICS OF NEOCORTICAL INTERACTIONS"

Connected through hyperedge HE-2 (induced by source paper "Statistical mechanics of neocortical interactions: Training and testing canonical momenta indicators of EEG"):
  with members:
    - "STATISTICAL MECHANICS OF COMBAT WITH HUMAN FACTORS"
    - "Statistical Mechanics of Nonlinear Nonequilibrium Financial Markets: Applications to Optimized Trading"
    - "MULTIPLE SCALES OF BRAIN-MIND INTERACTIONS"

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