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: "Stochastic Random or probabilistic but with some direction. For example the arrival of people at"
  Abstract: Simulated Annealing Search technique where a single trial solution is modified at random. An energy is defined which represents how good the solution is. The goal is to find the best solution by minimising the energy. Changes which lead to a lower energy are always accepted; an increase is probabilistically accepted. The probability is given by exp(E=k B T ). Where E is the change in energy, k B is a constant and T is the Temperature. Initially the temperature is high corresponding to a liquid or molten state where large changes are possible and it is progressively reduced using a cooling schedule so allowing smaller changes until the system solidifies at a low energy solution.

Connected through hyperedge HE-1 (induced by source paper "Evolution of Mapmaking: Learning, planning, and memory using Genetic Programming"):
  with members:
    - "Evolution of Iteration in Genetic Programming D a v d A The solution to many"
    - "The Automatic Programming of Agents that Learn Mental Models and Create Simple Plans of Action"
    - "The Evolution of Memory and Mental Models Using Genetic Programming build internal representations of their"
    - "learning easier tasks. More work is necessary in order to determine more precisely the relationship"
    - "Improving the Performance of Evolutionary Optimization by Dynamically Scaling the Evaluation Function"

Connected through hyperedge HE-2 (induced by source paper "Learning Monitoring Strategies: A Difficult Genetic Programming Application"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Monitoring in Embedded Agents"

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