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 "Category: Control, Navigation and Planning. Key words: Reinforcement learning, Exploration, Hidden state. Prefer oral presentation."):
  Abstract: This paper presents Fringe Exploration, a technique for efficient exploration in partially observable domains. The key idea, (applicable to many exploration techniques), is to keep statistics in the space of possible short-term memories, instead of in the agent's current state space. Experimental results in a partially observable maze and in a difficult driving task with visual routines show dramatic performance improvements.

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 "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Learning Probabilistic Automata with Variable Memory Length":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Machine Learning 27(1):51-68, 1997. Predicting nearly as well as the best pruning of a decision tree")
  Member "Learning to Use Selective Attention and Short-Term Memory in Sequential Tasks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces")

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