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 "A Formal Framework for Speedup Learning from Problems and Solutions"):
  Abstract: Speedup learning seeks to improve the computational efficiency of problem solving with experience. In this paper, we develop a formal framework for learning efficient problem solving from random problems and their solutions. We apply this framework to two different representations of learned knowledge, namely control rules and macro-operators, and prove theorems that identify sufficient conditions for learning in each representation. Our proofs are constructive in that they are accompanied with learning algorithms. Our framework captures both empirical and explanation-based speedup learning in a unified fashion. We illustrate our framework with implementations in two domains: symbolic integration and Eight Puzzle. This work integrates many strands of experimental and theoretical work in machine learning, including empirical learning of control rules, macro-operator learning,

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 "A Statistical Approach to Solving the EBL Utility Problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Probably Approximately Optimal Derivation Strategies")

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: Theory