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 COMPRESSION ALGORITHM FOR PROBABILITY TRANSITION MATRICES"
  Abstract: This paper describes a compression algorithm for probability transition matrices. The compressed matrix is itself a probability transition matrix. In general the compression is not error-free, but the error appears to be small even for high levels of compression.

Connected through hyperedge HE-1 (induced by source paper "Using Markov Chains to Analyze GAFOs"):
  with members:
    - "Island Model Genetic Algorithms and Linearly Separable Problems"
    - "Analyzing GAs Using Markov Models with Semantically Ordered and Lumped States"

Connected through hyperedge HE-2 (induced by source paper "An Overview of Evolutionary Computation"):
  with members:
    - "An Evolutionary Approach to Combinatorial Optimization Problems"
    - "EVOLVING REPRESENTATIONS OF DESIGN CASES AND THEIR USE IN CREATIVE DESIGN"
    - "In Proceedings of the 1997 Sian Kaan International Workshop on Neural Networks and Neurocontrol. Real-Valued"

Connected through hyperedge HE-3 (induced by source paper "Analyzing GAs Using Markov Models with Semantically Ordered and Lumped States"):
  with members:
    - "Using Markov Chains to Analyze GAFOs"

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