human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Locally Weighted Learning for Control"):
  Abstract: Lazy learning methods provide useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of complex systems. This paper surveys ways in which locally weighted learning, a type of lazy learning, has been applied by us to control tasks. We explain various forms that control tasks can take, and how this affects the choice of learning paradigm. The discussion section explores the interesting impact that explicitly remembering all previous experiences has on the problem of learning to control.

Includes members:
  Member "Issues in Using Function Approximation for Reinforcement Learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "On the Convergence of Stochastic Iterative Dynamic Programming Algorithms")
  Member "Control Systems Magazine, 14, 1, pp.57-71. Robot Juggling: An Implementation of Memory-based Learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming")
  Member "Online Learning with Random Representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "An Improved Algorithm for Incremental Induction of Decision Trees")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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: Reinforcement_Learning