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: "Improving Competence by Integrating Case-Based Reasoning and Heuristic Search"
  Abstract: We analyse the behaviour of a Propose & Revise architecture in the VT elevator design problem and we show that this problem solving method cannot solve all possible cases covered by the available domain knowledge. We investigate this problem and we show that this limitation is caused by the restricted search regime employed by the method and that the competence of the method cannot be improved by acquiring additional domain knowledge. We therefore propose an alternative design problem solver, which integrates case-based reasoning and heuristic search techniques and overcomes the competence-related limitations exhibited by the Propose & Revise architecture, while maintaining the same level of efficiency. We describe four algorithms for case-based design, which exploit both general properties of parametric design tasks and application specific heuristic knowledge.

Connected through hyperedge HE-1 (induced by source paper "Parametric Design Problem Solving"):
  with members:
    (none)

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