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: "Using Introspective Reasoning to Select Learning Strategies"
  Abstract: In order to learn effectively, a system must not only possess knowledge about the world and be able to improve that knowledge, but it also must introspectively reason about how it performs a given task and what particular pieces of knowledge it needs to improve its performance at the current task. Introspection requires a declaratflive representation of the reasoning performed by the system during the performance task. This paper presents a taxonomy of possible reasoning failures that can occur during this task, their declarative representations, and their associations with particular learning strategies. We propose a theory of Meta-XPs, which are explanation structures that help the system identify failure types and choose appropriate learning strategies in order to avoid similar mistakes in the future. A program called Meta-AQUA embodies the theory and processes examples in the domain of drug smuggling.

Connected through hyperedge HE-1 (induced by source paper "Incremental Learning of Explanation Patterns and their Indices"):
  with members:
    - "A theory of questions and question asking"
    - "Decision Models: A Theory of Volitional Explanation"
    - "Learning Indices for Schema Selection"
    - "A Goal-Based Approach to Intelligent Information Retrieval"

Connected through hyperedge HE-2 (induced by source paper "Indexing, Elaboration and Refinement: Incremental Learning of Explanatory Cases"):
  with members:
    - "A theory of questions and question asking"
    - "Abstract"
    - "Model-Based Learning of Structural Indices to Design Cases"
    - "Learning Indices for Schema Selection"

Connected through hyperedge HE-3 (induced by source paper "Decision Models: A Theory of Volitional Explanation"):
  with members:
    - "A theory of questions and question asking"
    - "Incremental Learning of Explanation Patterns and their Indices"
    - "Learning Indices for Schema Selection"

Connected through hyperedge HE-4 (induced by source paper "Abstract"):
  with members:
    (none)

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