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: "Trading Spaces: Computation, Representation and the Limits of Uninformed Learning"
  Abstract: fl Research on this paper was partly supported by a Senior Research Leave fellowship granted by the Joint Council (SERC/MRC/ESRC) Cognitive Science Human Computer Interaction Initiative to one of the authors (Clark). Thanks to the Initiative for that support. y The order of names is arbitrary.

Connected through hyperedge HE-1 (induced by source paper "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."):
  with members:
    - "Measuring the Difficulty of Specific Learning Problems"
    - "Discovering Complex Othello Strategies Through Evolutionary Neural Networks"
    - "USING MARKER-BASED GENETIC ENCODING OF NEURAL NETWORKS TO EVOLVE FINITE-STATE BEHAVIOUR"
    - "Evolving Obstacle Avoidance Behavior in a Robot Arm"
    - "A Comparison of Selection Schemes used in Genetic Algorithms"
    - "Determining Successful Negotiation Strategies: An Evolutionary Approach"
    - "Genetic Programming and Redundancy"
    - "Island Model Genetic Algorithms and Linearly Separable Problems"

Connected through hyperedge HE-2 (induced by source paper "Truth-from-Trash Learning and the Mobot"):
  with members:
    - "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex."
    - "Parity: The Problem that Won't Go Away"

Connected through hyperedge HE-3 (induced by source paper "Simple Genetic Programming for Supervised Learning Problems"):
  with members:
    - "Measuring the Difficulty of Specific Learning Problems"

Connected through hyperedge HE-4 (induced by source paper "Measuring the Difficulty of Specific Learning Problems"):
  with members:
    - "Simple Genetic Programming for Supervised Learning Problems"
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Interpretable Neural Networks with BP-SOM"
    - "Avoiding Overfitting with BP-SOM"
    - "Is Transfer Inductive?"

Connected through hyperedge HE-5 (induced by source paper "Statistical Biases in Backpropagation Learning  Keywords: Cognitive Science, Pattern recognition"):
  with members:
    - "Is Transfer Inductive?"

Connected through hyperedge HE-6 (induced by source paper "There is No Free Lunch but the Starter is Cheap: Generalisation from First Principles"):
  with members:
    - "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex."
    - "Separability is a Learner's Best Friend"

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