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 "Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition"):
  Abstract: This paper describes the MAXQ method for hierarchical reinforcement learning based on a hierarchical decomposition of the value function and derives conditions under which the MAXQ decomposition can represent the optimal value function. We show that for certain execution models, the MAXQ decomposition will produce better policies than Feudal Q learning.

Includes members:
  Member "Transfer of Learning by Composing Solutions of Elemental Sequential Tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Robust Reinforcement Learning in Motion Planning")
  Member "On the Convergence of Stochastic Iterative Dynamic Programming Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Towards a Reactive Critic")
  Member "Reinforcement Learning with Hierarchies of Machines":
    also connected through other hyperedges:
      (none)
  Member "Between MDPs and Semi-MDPs: Learning, Planning, and Representing Knowledge at Multiple Temporal Scales":
    also connected through other hyperedges:
      (none)

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