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 "Analysis of Some Incremental Variants of Policy Iteration: First Steps Toward Understanding Actor-Critic Learning Systems"):
  Abstract: Northeastern University College of Computer Science Technical Report NU-CCS-93-11 fl We gratefully acknowledge the substantial contributions to this effort provided by Andy Barto, who sparked our original interest in these questions and whose continued encouragement and insightful comments and criticisms have helped us greatly. Recent discussions with Satinder Singh and Vijay Gullapalli have also had a helpful impact on this work. Special thanks also to Rich Sutton, who has influenced our thinking on this subject in numerous ways. This work was supported by Grant IRI-8921275 from the National Science Foundation and by the U. S. Air Force.

Includes members:
  Member "An Upper Bound on the Loss from Approximate Optimal-Value Functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Learning to Act using Real-Time Dynamic Programming")
  Member "Asynchronous Modified Policy Iteration with Single-sided Updates":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Generalized Markov Decision Processes: Dynamic-programming and Reinforcement-learning Algorithms")

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