human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Issues in Goal-Driven Explanation"):
  Abstract: When a reasoner explains surprising events for its internal use, a key motivation for explaining is to perform learning that will facilitate the achievement of its goals. Human explainers use a range of strategies to build explanations, including both internal reasoning and external information search, and goal-based considerations have a profound effect on their choices of when and how to pursue explanations. However, standard AI models of explanation rely on goal-neutral use of a single fixed strategy|generally backwards chaining|to build their explanations. This paper argues that explanation should be modeled as a goal-driven learning process for gathering and transforming information, and discusses the issues involved in developing an active multi-strategy process for goal-driven explanation.

Includes members:
  Member "Introspective reasoning using meta-explanations for multistrategy learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Integrating Creativity and Reading: A Functional Approach")
  Member "INFERENTIAL THEORY OF LEARNING: Developing Foundations for Multistrategy Learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Context-Based Similarity Applied to Retrieval of Relevant Cases")
  Member "Goal-Driven Learning: Fundamental Issues (A Symposium Report)":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "BECOMING AN EXPERT CASE-BASED REASONER: LEARNING TO ADAPT PRIOR CASES")
  Member "AN ARCHITECTURE FOR GOAL-DRIVEN EXPLANATION":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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