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: "Type Inheritance in Strongly Typed Genetic Programming"
  Abstract: This paper appears as chapter 18 of Kenneth E. Kinnear, Jr. and Peter J. Angeline, editors Advances in Genetic Programming 2, MIT Press, 1996. Abstract Genetic Programming (GP) is an automatic method for generating computer programs, which are stored as data structures and manipulated to evolve better programs. An extension restricting the search space is Strongly Typed Genetic Programming (STGP), which has, as a basic premise, the removal of closure by typing both the arguments and return values of functions, and by also typing the terminal set. A restriction of STGP is that there are only two levels of typing. We extend STGP by allowing a type hierarchy, which allows more than two levels of typing.

Connected through hyperedge HE-1 (induced by source paper "A Comparison of Random Search versus Genetic Programming as Engines for Collective Adaptation"):
  with members:
    - "Strongly Typed Genetic Programming"
    - "Duplication of Coding Segments in Genetic Programming"

Connected through hyperedge HE-2 (induced by source paper "ABSTRACT"):
  with members:
    - "Performance Enhanced Genetic Programming"

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"
    - "Modeling Distributed Search via Social Insects"
    - "1 GP-COM: A Distributed, Component-Based Genetic Programming System in C++"
    - "Program Optimization for Faster Genetic Programming"

Connected through hyperedge HE-4 (induced by source paper "Clique Detection via Genetic Programming  Topics in Combinatorial Optimization"):
  with members:
    (none)

Connected through hyperedge HE-5 (induced by source paper "Entailment for Specification Refinement"):
  with members:
    - "Strongly Typed Genetic Programming"
    - "Duplication of Coding Segments in Genetic Programming"
    - "Induction and Recapitulation of Deep Musical Structure"

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