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: "AN ARCHITECTURE FOR GOAL-DRIVEN EXPLANATION"
  Abstract: In complex and changing environments explanation must be a a dynamic and goal-driven process. This paper discusses an evolving system implementing a novel model of explanation generation | Goal-Driven Interactive Explanation | that models explanation as a goal-driven, multi-strategy, situated process inter-weaving reasoning with action. We describe a preliminary implementation of this model in gobie, a system that generates explanations for its internal use to support plan generation and execution.

Connected through hyperedge HE-1 (induced by source paper "Issues in Goal-Driven Explanation"):
  with members:
    - "Introspective reasoning using meta-explanations for multistrategy learning"
    - "INFERENTIAL THEORY OF LEARNING: Developing Foundations for Multistrategy Learning"
    - "Goal-Driven Learning: Fundamental Issues (A Symposium Report)"

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