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: "Modeling Case-based Planning for Repairing Reasoning Failures"
  Abstract: One application of models of reasoning behavior is to allow a reasoner to introspectively detect and repair failures of its own reasoning process. We address the issues of the transferability of such models versus the specificity of the knowledge in them, the kinds of knowledge needed for self-modeling and how that knowledge is structured, and the evaluation of introspective reasoning systems. We present the ROBBIE system which implements a model of its planning processes to improve the planner in response to reasoning failures. We show how ROBBIE's hierarchical model balances model generality with access to implementation-specific details, and discuss the qualitative and quantitative measures we have used for evaluating its introspective component.

Connected through hyperedge HE-1 (induced by source paper "BECOMING AN EXPERT CASE-BASED REASONER: LEARNING TO ADAPT PRIOR CASES"):
  with members:
    - "Towards A Computer Model of Memory Search Strategy Learning"
    - "Learning Adaptation Strategies by Introspective Reasoning about Memory Search"
    - "Goal-Driven Learning: Fundamental Issues (A Symposium Report)"

Connected through hyperedge HE-2 (induced by source paper "Abstract"):
  with members:
    - "Representing Self-knowledge for Introspection about Memory Search"
    - "Introspective reasoning using meta-explanations for multistrategy learning"
    - "Using Knowledge of Cognitive Behavior to Learn from Failure"

Connected through hyperedge HE-3 (induced by source paper "Using Knowledge of Cognitive Behavior to Learn from Failure"):
  with members:
    - "Abstract"

Connected through hyperedge HE-4 (induced by source paper "Introspective reasoning using meta-explanations for multistrategy learning"):
  with members:
    - "Abstract"
    - "Integrating Creativity and Reading: A Functional Approach"
    - "Role of Ontology in Creative Understanding"
    - "Abstract"
    - "A Functional Theory of Creative Reading"
    - "Towards A Computer Model of Memory Search Strategy Learning"
    - "Issues in Goal-Driven Explanation"
    - "Learning Problem-Solving Concepts by Reflecting on Problem Solving"

Connected through hyperedge HE-5 (induced by source paper "Abstract"):
  with members:
    - "Representing Self-knowledge for Introspection about Memory Search"

Connected through hyperedge HE-6 (induced by source paper "Generic Teleological Mechanisms and their Use in Case Adaptation"):
  with members:
    - "A Model-Based Approach to Blame-Assignment in Design"
    - "KRITIK: AN EARLY CASE-BASED DESIGN SYSTEM"
    - "Model-Based Learning of Structural Indices to Design Cases"
    - "The Role of Generic Models in Conceptual Change"
    - "Learning Generic Mechanisms from Experiences for Analogical Reasoning"
    - "Discovery of Physical Principles from Design Experiences"

Connected through hyperedge HE-7 (induced by source paper "Using Case-Based Reasoning for Mobile Robot Navigation"):
  with members:
    - "A Case-Based Approach to Reactive Control for Autonomous Robots"

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