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 Parallel Genetic Algorithms"
  Abstract: IlliGAL Report No. 97003 May 1997

Connected through hyperedge HE-1 (induced by source paper "Speeding up Genetic Programming: A Parallel BSP implementation the Bulk Synchronous Parallel Pro gramming (BSP)"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Evolution in Time and Space The Parallel Genetic Algorithm"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Island Model Genetic Algorithms and Linearly Separable Problems"
    - "A Study of Genetic Algorithms to Find Approximate Solutions to Hard 3CNF Problems"
    - "Recombination Operator, its Correlation to the Fitness Landscape and Search Performance"
    - "Genetic Algorithm Programming Environments"
    - "Staged Hybrid Genetic Search for Seismic Data Imaging"
    - "The Schema Theorem and Price's Theorem"
    - "Self-Adaptation in Genetic Algorithms of external parameters of a GA is seen as a first"

Connected through hyperedge HE-3 (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-4 (induced by source paper "Genetic Algorithms for Combinatorial Optimization: The Assembly Line Balancing Problem"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Distribution Category:  A Parallel Genetic Algorithm for the Set Partitioning Problem"

Connected through hyperedge HE-5 (induced by source paper "Distribution Category:  A Parallel Genetic Algorithm for the Set Partitioning Problem"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Surgery"
    - "A Comparative Study of Genetic Search"
    - "Scheduling Maintenance of Electrical Power Transmission Networks Using Genetic Programming"
    - "Genetic Algorithms for Combinatorial Optimization: The Assembly Line Balancing Problem"
    - "An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms"
    - "On the Virtues of Parameterized Uniform Crossover"
    - "As mentioned in the introduction, an encod-ing/crossover pair makes a spectrum of geographical linkages. A"

Connected through hyperedge HE-6 (induced by source paper "An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms"):
  with members:
    - "Using Neural Networks and Genetic Algorithms as Heuristics for NP-Complete Problems"
    - "Evolution in Time and Space The Parallel Genetic Algorithm"
    - "Local Selection"

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