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: "A theory of questions and question asking"

Connected through hyperedge HE-1 (induced by source paper "Integrating Creativity and Reading: A Functional Approach"):
  with members:
    - "Introspective reasoning using meta-explanations for multistrategy learning"
    - "CASE-BASED CREATIVE DESIGN"
    - "Role of Ontology in Creative Understanding"

Connected through hyperedge HE-2 (induced by source paper "Incremental Learning of Explanation Patterns and their Indices"):
  with members:
    - "Using Introspective Reasoning to Select Learning Strategies"
    - "Decision Models: A Theory of Volitional Explanation"
    - "Learning Indices for Schema Selection"
    - "A Goal-Based Approach to Intelligent Information Retrieval"

Connected through hyperedge HE-3 (induced by source paper "Indexing, Elaboration and Refinement: Incremental Learning of Explanatory Cases"):
  with members:
    - "Using Introspective Reasoning to Select Learning Strategies"
    - "Abstract"
    - "Model-Based Learning of Structural Indices to Design Cases"
    - "Learning Indices for Schema Selection"

Connected through hyperedge HE-4 (induced by source paper "Decision Models: A Theory of Volitional Explanation"):
  with members:
    - "Using Introspective Reasoning to Select Learning Strategies"
    - "Incremental Learning of Explanation Patterns and their Indices"
    - "Learning Indices for Schema Selection"

Connected through hyperedge HE-5 (induced by source paper "The Use of Explicit Goals for Knowledge to Guide Inference and Learning"):
  with members:
    - "Opportunistic Reasoning: A Design Perspective"
    - "INFERENTIAL THEORY OF LEARNING: Developing Foundations for Multistrategy Learning"
    - "A Functional Theory of Creative Reading"
    - "an Opportunistic Enterprise"
    - "A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems"
    - "Case-Based Planning to Learn"
    - "A Goal-Based Approach to Intelligent Information Retrieval"

Connected through hyperedge HE-6 (induced by source paper "Abstract"):
  with members:
    - "Introspective reasoning using meta-explanations for multistrategy learning"
    - "Indexing, Elaboration and Refinement: Incremental Learning of Explanatory Cases"
    - "Choosing Learning Strategies to Achieve Learning Goals"

Connected through hyperedge HE-7 (induced by source paper "A Functional Theory of Creative Reading"):
  with members:
    - "Introspective reasoning using meta-explanations for multistrategy learning"
    - "CASE-BASED CREATIVE DESIGN"
    - "The Use of Explicit Goals for Knowledge to Guide Inference and Learning"

Connected through hyperedge HE-8 (induced by source paper "INFERENTIAL THEORY OF LEARNING: Developing Foundations for Multistrategy Learning"):
  with members:
    - "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley."
    - "In Machine Learning: A Multistrategy Approach, Vol. IV  Macro and Micro Perspectives of Multistrategy Learning"
    - "The Use of Explicit Goals for Knowledge to Guide Inference and Learning"
    - "Issues in Goal-Driven Explanation"
    - "Context-Based Similarity Applied to Retrieval of Relevant Cases"
    - "Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification"
    - "Machine Learning and Inference"
    - "Machine Learning and Inference"

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