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 "Efficient dynamic-programming updates in partially observable Markov decision processes"):
  Abstract: We examine the problem of performing exact dynamic-programming updates in partially observable Markov decision processes (pomdps) from a computational complexity viewpoint. Dynamic-programming updates are a crucial operation in a wide range of pomdp solution methods and we find that it is intractable to perform these updates on piecewise-linear convex value functions for general pomdps. We offer a new algorithm, called the witness algorithm, which can compute updated value functions efficiently on a restricted class of pomdps in which the number of linear facets is not too great. We compare the witness algorithm to existing algorithms analytically and empirically and find that it is the fastest algorithm over a wide range of pomdp sizes.

Includes members:
  Member "Learning policies for partially observable environments: Scaling up":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Acting under Uncertainty: Discrete Bayesian Models for Mobile-Robot Navigation")
  Member "Approximating Optimal Policies for Partially Observable Stochastic Domains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Acting under Uncertainty: Discrete Bayesian Models for Mobile-Robot Navigation")
  Member "Incremental methods for computing bounds in partially observable Markov decision processes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Approximating Optimal Policies for Partially Observable Stochastic Domains")

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