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 "Auto-exploratory Average Reward Reinforcement Learning"):
  Abstract: We introduce a model-based average reward Reinforcement Learning method called H-learning and compare it with its discounted counterpart, Adaptive Real-Time Dynamic Programming, in a simulated robot scheduling task. We also introduce an extension to H-learning, which automatically explores the unexplored parts of the state space, while always choosing greedy actions with respect to the current value function. We show that this "Auto-exploratory H-learning" performs better than the original H-learning under previously studied exploration methods such as random, recency-based, or counter-based exploration.

Includes members:
  Member "Learning to Act using Real-Time Dynamic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "On the Complexity of Solving Markov Decision Problems")
  Member "Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Learning to Act using Real-Time Dynamic Programming")
  Member "Generalized Markov Decision Processes: Dynamic-programming and Reinforcement-learning Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Acting under Uncertainty: Discrete Bayesian Models for Mobile-Robot Navigation")
  Member "Reinforcement Learning Algorithms for Average-Payoff Markovian Decision Processes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Learning to Act using Real-Time Dynamic Programming")

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