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: "Specialization in Populations of Artificial Neural Networks"
  Abstract: Specialization in populations of artificial neural networks is studied. Organisms with both fixed and evolvable fitness formulae are placed in isolated and shared environments, and the emerged behaviors are compared. An evolvable fitness formula specifies, that the evaluation measure is let free to evolve, and we obtain co-evolution of the expressed behavior and the individual evolvable fitness formula. In an isolated environment a generalist behavior emerges when organisms have a fixed fitness formula, and a specialist behavior emerges when organisms have individual evolvable fitness formulae. A population diversification analysis shows, that almost all organisms in a population in an isolated environment converge towards the same behavioral strategy, while we find, that competition can act to provide population diversification in populations of organisms in a shared environment.

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"
    - "Trading Spaces: Computation, Representation and the Limits of Uninformed Learning"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "Specialization under Social Conditions in Shared Environments"):
  with members:
    - "Generalist and Specialist Behavior Due to Individual Energy Extracting Abilities."

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: Genetic_Algorithms