human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Abstract"
  Abstract: Given an arbitrary learning situation, it is difficult to determine the most appropriate learning strategy. The goal of this research is to provide a general representation and processing framework for introspective reasoning for strategy selection. The learning framework for an introspective system is to perform some reasoning task. As it does, the system also records a trace of the reasoning itself, along with the results of such reasoning. If a reasoning failure occurs, the system retrieves and applies an introspective explanation of the failure in order to understand the error and repair the knowledge base. A knowledge structure called a Meta-Explanation Pattern is used to both explain how conclusions are derived and why such conclusions fail. If reasoning is represented in an explicit, declarative manner, the system can examine its own reasoning, analyze its reasoning failures, identify what it needs to learn, and select appropriate learning strategies in order to learn the required knowledge without overreli ance on the programmer.

Connected through hyperedge HE-1 (induced by source paper "Using Introspective Reasoning to Select Learning Strategies"):
  with members:
    - "Decision Models: A Theory of Volitional Explanation"
    - "Incremental Learning of Explanation Patterns and their Indices"
    - "Indexing, Elaboration and Refinement: Incremental Learning of Explanatory Cases"

Question: Please tell me which class the center node 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: Case_Based