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 "Learning To Play the Game of Chess"):
  Abstract: This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial neural networks. It integrates inductive neural network learning, temporal differencing, and a variant of explanation-based learning. Performance results illustrate some of the strengths and weaknesses of this approach.

Includes members:
  Member "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "TDLeaf(): Combining Temporal Difference learning with game-tree search.")
  Member "Generalization in Reinforcement Learning: Safely Approximating the Value Function":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A Reinforcement Learning Approach to Job-shop Scheduling")
  Member "Issues in Using Function Approximation for Reinforcement Learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "On the Convergence of Stochastic Iterative Dynamic Programming Algorithms")
  Member "TDLeaf(): Combining Temporal Difference learning with game-tree search.":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,")
  Member "NeuroDraughts: the role of representation, search, training regime and architecture in a TD draughts player":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,")
  Member "KnightCap: A chess program that learns by combining TD() with minimax search":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,")
  Member "Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "Quick 'n' Dirty Generalization For Mobile Robot Learning Content Areas: robotics, reinforcement learning, machine learning,")

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