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 with Imitation in Heterogeneous Multi-Agent Systems"):
  Abstract: The application of decision making and learning algorithms to multi-agent systems presents many interestingresearch challenges and opportunities. Among these is the ability for agents to learn how to act by observing or imitating other agents. We describe an algorithm, the IQ-algorithm, that integrates imitation with Q-learning. Roughly, a Q-learner uses the observations it has made of an expert agent to bias its exploration in promising directions. This algorithm goes beyond previous work in this direction by relaxing the oft-made assumptions that the learner (observer) and the expert (observed agent) share the same objectives and abilities. Our preliminary experiments demonstrate significant transfer between agents using the IQ-model and in many cases reductions in training time.

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 "Markov games as a framework for multi-agent reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Learning Conventions in Multiagent Stochastic Domains using Likelihood Estimates")
  Member "Reinforcement Learning: A Survey":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm")
  Member "Learning to coordinate without sharing information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Adaptive Load Balancing: A Study in Multi-Agent 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