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 "Reinforcement Learning in the Multi-Robot Domain"):
  Abstract: This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environemnts such as in the complex concurrent multi-robot learning domain. The methodology involves minimizing the learning space through the use behaviors and conditions, and dealing with the credit assignment problem through shaped reinforcement in the form of heterogeneous reinforcement functions and progress estimators. We experimentally validate the ap proach on a group of four mobile robots learning a foraging task.

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 "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "TDLeaf(): Combining Temporal Difference learning with game-tree search.")
  Member "Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Adaptive Load Balancing: A Study in Multi-Agent Learning")
  Member "Control Systems Magazine, 14, 1, pp.57-71. Robot Juggling: An Implementation of Memory-based Learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming")
  Member "Using Communication to Reduce Locality in Distributed Multi-Agent Learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents")

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