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 "Redesigning control knowledge of knowledge-based systems: machine learning meets knowledge engineering"):
  Abstract: Machine learning and knowledge engineering have always been strongly related, but the introduction of new representations in knowledge engineering has created a gap between them. This paper describes research aimed at applying machine learning techniques to the current knowledge engineering representations. We propose a system that redesigns a part of a knowledge based system, the so called control knowledge. We claim a strong similarity between redesign of knowledge based systems and incremental machine learning. Finally we will relate this work to existing research.

Includes members:
  Member "Learning Problem-Solving Concepts by Reflecting on Problem Solving":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Introspective reasoning using meta-explanations for multistrategy learning")
  Member "A Performance Model for Knowledge-based Systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A utility-based approach to learning in a mixed Case-Based and Model-Based Reasoning architecture")

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