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: "Design and Implementation of a Replay Framework based on a Partial Order Planner"
  Abstract: In this paper we describe the design and implementation of the derivation replay framework, dersnlp+ebl (Derivational snlp+ebl), which is based within a partial order planner. dersnlp+ebl replays previous plan derivations by first repeating its earlier decisions in the context of the new problem situation, then extending the replayed path to obtain a complete solution for the new problem. When the replayed path cannot be extended into a new solution, explanation-based learning (ebl) techniques are employed to identify the features of the new problem which prevent this extension. These features are then added as censors on the retrieval of the stored case. To keep retrieval costs low, dersnlp+ebl normally stores plan derivations for individual goals, and replays one or more of these derivations in solving multi-goal problems. Cases covering multiple goals are stored only when subplans for individual goals cannot be successfully merged. The aim in constructing the case library is to predict these goal interactions and to store a multi-goal case for each set of negatively interacting goals. We provide empirical results demonstrating the effectiveness of dersnlp+ebl in improving planning performance on randomly-generated problems drawn from a complex domain.

Connected through hyperedge HE-1 (induced by source paper "A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems"):
  with members:
    - "AN EMPIRICAL APPROACH TO SOLVING THE GENERAL UTILITY PROBLEM IN SPEEDUP LEARNING"
    - "The Use of Explicit Goals for Knowledge to Guide Inference and Learning"
    - "An Explanation-Based Approach to Improve Retrieval in Case-Based Planning"
    - "A utility-based approach to learning in a mixed Case-Based and Model-Based Reasoning architecture"

Connected through hyperedge HE-2 (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"
    - "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"
    - "Automatic Storage and Indexing of Plan Derivations based on Replay Failures"

Connected through hyperedge HE-3 (induced by source paper "An Explanation-Based Approach to Improve Retrieval in Case-Based Planning"):
  with members:
    - "Evaluating the Effectiveness of Derivation Replay in Partial-order vs State-space Planning"
    - "A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems"

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