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: "Improving Tactical Plans with Genetic Algorithms"

Connected through hyperedge HE-1 (induced by source paper "EVOLVING ROBOT BEHAVIORS"):
  with members:
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "Genetics-based Machine Learning and Behaviour Based Robotics: A New Synthesis complexity grows, the learning task"
    - "Using a Genetic Algorithm to Learn Strategies for Collision Avoidance and Local Navigation"
    - "Simulation-Assisted Learning by Competition: Effects of Noise Differences Between Training Model and Target Environment"

Connected through hyperedge HE-2 (induced by source paper "Evaluation and Selection of Biases in Machine Learning"):
  with members:
    - "Irrelevant Features and the Subset Selection Problem"
    - "Evolution-based Discovery of Hierarchical Behaviors"
    - "#1 Robust Feature Selection Algorithms"
    - "Model selection using measure functions"
    - "Dlab: A Declarative Language Bias Formalism"
    - "Utilizing Prior Concepts for Learning"

Connected through hyperedge HE-3 (induced by source paper "EVOLUTIONARY ALGORITHMS IN ROBOTICS"):
  with members:
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "Genetics-based Machine Learning and Behaviour Based Robotics: A New Synthesis complexity grows, the learning task"
    - "Simulation-Assisted Learning by Competition: Effects of Noise Differences Between Training Model and Target Environment"

Connected through hyperedge HE-4 (induced by source paper "USING A GENETIC ALGORITHM TO LEARN BEHAVIORS FOR AUTONOMOUS VEHICLES"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "ROBO-SHEPHERD: LEARNING COMPLEX ROBOTIC BEHAVIORS"
    - "ROBOT LEARNING WITH PARALLEL GENETIC ALGORITHMS ON NETWORKED COMPUTERS"
    - "ADAPTIVE TESTING OF CONTROLLERS FOR AUTONOMOUS VEHICLES"

Connected through hyperedge HE-5 (induced by source paper "Using a Genetic Algorithm to Learn Strategies for Collision Avoidance and Local Navigation"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "LEARNING ROBOT BEHAVIORS USING GENETIC ALGORITHMS"
    - "Explanations of Empirically Derived Reactive Plans"
    - "Simulation-Assisted Learning by Competition: Effects of Noise Differences Between Training Model and Target Environment"
    - "EVOLVING ROBOT BEHAVIORS"
    - "ADAPTIVE TESTING OF CONTROLLERS FOR AUTONOMOUS VEHICLES"
    - "An Evolutionary Approach to Learning in Robots"

Connected through hyperedge HE-6 (induced by source paper "Explanations of Empirically Derived Reactive Plans"):
  with members:
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "Using a Genetic Algorithm to Learn Strategies for Collision Avoidance and Local Navigation"
    - "LEARNING CONCEPTS BY ASKING QUESTIONS"
    - "Simulation-Assisted Learning by Competition: Effects of Noise Differences Between Training Model and Target Environment"
    - "AN ENHANCER FOR REACTIVE PLANS"

Connected through hyperedge HE-7 (induced by source paper "The Exploitation of Cooperation in Iterated Prisoner's Dilemma"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"

Connected through hyperedge HE-8 (induced by source paper "LEARNING ROBOT BEHAVIORS USING GENETIC ALGORITHMS"):
  with members:
    - "Cooperative Bayesian and Case-Based Reasoning for Solving Multiagent Planning Tasks"
    - "Learning Sequential Decision Rules Using Simulation Models and Competition"
    - "Using a Genetic Algorithm to Learn Strategies for Collision Avoidance and Local Navigation"
    - "ROBO-SHEPHERD: LEARNING COMPLEX ROBOTIC BEHAVIORS"
    - "ROBOT LEARNING WITH PARALLEL GENETIC ALGORITHMS ON NETWORKED COMPUTERS"
    - "Simulation-Assisted Learning by Competition: Effects of Noise Differences Between Training Model and Target Environment"
    - "AN ENHANCER FOR REACTIVE PLANS"

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