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: "Evolving nonTrivial Behaviors on Real Robots: an Autonomous Robot that Picks up Objects"
  Abstract: Recently, a new approach that involves a form of simulated evolution has been proposed for the building of autonomous robots. However, it is still not clear if this approach may be adequate to face real life problems. In this paper we show how control systems that perform a nontrivial sequence of behaviors can be obtained with this methodology by carefully designing the conditions in which the evolutionary process operates. In the experiment described in the paper, a mobile robot is trained to locate, recognize, and grasp a target object. The controller of the robot has been evolved in simulation and then downloaded and tested on the real robot.

Connected through hyperedge HE-1 (induced by source paper "An Artificial Life Model for Investigating the Evolution of Modularity"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Issues in Evolutionary Robotics"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Evolving Obstacle Avoidance Behavior in a Robot Arm"
    - "The Evolutionary Cost of Learning"
    - "Analysis of Neurocontrollers Designed by Simulated Evolution"
    - "Selection for Wandering Behavior in a Small Robot"
    - "A Hybrid GP/GA Approach for Co-evolving Controllers and Robot Bodies to Achieve Fitness-Specified Tasks"
    - "Environmental Effects on Minimal Behaviors in the Minimat World"
    - "Evolving Visually Guided Robots"

Connected through hyperedge HE-3 (induced by source paper "Selection for Wandering Behavior in a Small Robot"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "Issues in Evolutionary Robotics"

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