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: "Automatic Storage and Indexing of Plan Derivations based on Replay Failures"
  Abstract: When a case-based planner is retrieving a previous case in preparation for solving a new similar problem, it is often not aware of all of the implicit features of the new problem situation which determine if a particular case may be successfully applied. This means that some cases may fail to improve the planner's performance. By detecting and explaining these case failures as they occur, retrieval may be improved incrementally. In this paper we provide a definition of case failure for the case-based planner, dersnlp (derivation replay in snlp), which solves new problems by replaying its previous plan derivations. We provide explanation-based learning (EBL) techniques for detecting and constructing the reasons for the case failure. We also describe how the case library is organized so as to incorporate this failure information as it is produced. Finally we present an empirical study which demonstrates the effectiveness of this approach in improving the performance of dersnlp.

Connected through hyperedge HE-1 (induced by source paper "Evaluating the Effectiveness of Derivation Replay in Partial-order vs State-space Planning"):
  with members:
    - "Storing and Indexing Plan Derivations through Explanation-based Analysis of Retrieval Failures"
    - "Design and Implementation of a Replay Framework based on a Partial Order Planner"
    - "An Explanation-Based Approach to Improve Retrieval in Case-Based Planning"
    - "Analysis and Empirical Studies of Derivational Analogy"
    - "Merge Strategies for Multiple Case Plan Replay"

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