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: "Entailment for Specification Refinement"
  Abstract: Specification refinement is part of formal program derivation, a method by which software is directly constructed from a provably correct specification. Because program derivation is an intensive manual exercise used for critical software systems, an automated approach would allow it to be viable for many other types of software systems. The goal of this research is to determine if genetic programming (GP) can be used to automate the specification refinement process. The initial steps toward this goal are to show that a well-known proof logic for program derivation can be encoded such that a GP-based system can infer sentences in the logic for proof of a particular sentence. The results are promising and indicate that GP can be useful in aiding pro gram derivation.

Connected through hyperedge HE-1 (induced by source paper "Type Inheritance in Strongly Typed Genetic Programming"):
  with members:
    - "Strongly Typed Genetic Programming"
    - "A Comparison of Random Search versus Genetic Programming as Engines for Collective Adaptation"
    - "Modeling Distributed Search via Social Insects"
    - "Augmenting Collective Adaptation with Simple Process Agents"
    - "ABSTRACT"
    - "Clique Detection via Genetic Programming  Topics in Combinatorial Optimization"

Connected through hyperedge HE-2 (induced by source paper "Duplication of Coding Segments in Genetic Programming"):
  with members:
    - "A Comparison of Random Search versus Genetic Programming as Engines for Collective Adaptation"
    - "A Survey of Intron Research in Genetics"
    - "Modeling Distributed Search via Social Insects"
    - "Augmenting Collective Adaptation with Simple Process Agents"
    - "A comparison of the fixed and floating building block representation in the genetic algorithm"

Connected through hyperedge HE-3 (induced by source paper "Strongly Typed Genetic Programming"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Towards Automatic Discovery of Building Blocks in Genetic Programming"
    - "A Methodology for Processing Problem Constraints in Genetic Programming"
    - "A Simulation of Adaptive Agents in a Hostile Environment"
    - "A Comparison of Random Search versus Genetic Programming as Engines for Collective Adaptation"
    - "Type Inheritance in Strongly Typed Genetic Programming"
    - "Modeling Distributed Search via Social Insects"
    - "1 GP-COM: A Distributed, Component-Based Genetic Programming System in C++"

Connected through hyperedge HE-4 (induced by source paper "Induction and Recapitulation of Deep Musical Structure"):
  with members:
    - "Evolution of Pseudo-colouring Algorithms for Image Enhancement with Interactive Genetic Programming"
    - "GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters"
    - "Automated Fitness Raters for the GP-Music System"

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