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 "Adding Memory to XCS"):
  Abstract: We add internal memory to the XCS classifier system. We then test XCS with internal memory, named XCSM, in non-Markovian environments with two and four aliasing states. Experimental results show that XCSM can easily converge to optimal solutions in simple environments; moreover, XCSM's performance is very stable with respect to the size of the internal memory involved in learning. However, the results we present evidence that in more complex non-Markovian environments, XCSM may fail to evolve an optimal solution. Our results suggest that this happens because, the exploration strategies currently employed with XCS, are not adequate to guarantee the convergence to an optimal policy with XCSM, in complex non-Markovian environments.

Includes members:
  Member "Reinforcement Learning: A Survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Reinforcement Learning with Imitation in Heterogeneous Multi-Agent Systems")
  Member "A Study of the Generalization Capabilities of XCS":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "GENETIC AND NON GENETIC OPERATORS IN ALECSYS")

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