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: "A Survey of Evolution Strategies"

Connected through hyperedge HE-1 (induced by source paper "Crossover or Mutation?"):
  with members:
    - "Generation Gaps Revisited"
    - "An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms"
    - "On the Virtues of Parameterized Uniform Crossover"
    - "A STUDY OF CROSSOVER OPERATORS IN GENETIC PROGRAMMING"

Connected through hyperedge HE-2 (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-3 (induced by source paper "A Sampling-Based Heuristic for Tree Search Applied to Grammar Induction"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "A Stochastic Search Approach to Grammar Induction"
    - "New Evidence Driven State Merging Algorithm"

Connected through hyperedge HE-4 (induced by source paper "Adaptive Strategy Selection for Concept Learning"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Using Genetic Algorithms for Supervised Concept Learning"

Connected through hyperedge HE-5 (induced by source paper "Strategy Adaptation by Competing Subpopulations"):
  with members:
    - "Self-Adaptation in Genetic Algorithms of external parameters of a GA is seen as a first"

Connected through hyperedge HE-6 (induced by source paper "Evolution of Non-Deterministic Incremental Algorithms as a New Approach for Search in State Spaces"):
  with members:
    - "A Stochastic Search Approach to Grammar Induction"
    - "Dynamic Parameter Encoding for Genetic Algorithms"
    - "Evolving Non-Determinism: An Inventive and Efficient Tool for Optimization and Discovery of Strategies"
    - "Incremental Co-evolution of Organisms: A New Approach for Optimization and Discovery of Strategies"
    - "Evolving Sorting Networks using Genetic Programming and Rapidly Reconfigurable Field-Programmable Gate Arrays Convergent Design, L.L.C."
    - "Use of Architecture-Altering Operations to Dynamically Adapt a Three-Way Analog Source Identification Circuit to Accommodate"

Connected through hyperedge HE-7 (induced by source paper "Recombination Operator, its Correlation to the Fitness Landscape and Search Performance"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Evolution in Time and Space The Parallel Genetic Algorithm"
    - "Genetic Programming of Minimal Neural Nets Using Occam's Razor"
    - "On the Virtues of Parameterized Uniform Crossover"

Connected through hyperedge HE-8 (induced by source paper "EVOLVING REPRESENTATIONS OF DESIGN CASES AND THEIR USE IN CREATIVE DESIGN"):
  with members:
    - "EMERGENT BEHAVIOUR IN CO-EVOLUTIONARY DESIGN"
    - "An Overview of Evolutionary Computation"

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