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: "Using Case-Based Reasoning to Acquire User Scheduling Preferences that Change over Time"
  Abstract: Production/Manufacturing scheduling typically involves the acquisition of user optimization preferences. The ill-structuredness of both the problem space and the desired objectives make practical scheduling problems difficult to formalize and costly to solve, especially when problem configurations and user optimization preferences change over time. This paper advocates an incremental revision framework for improving schedule quality and incorporating user dynamically changing preferences through Case-Based Reasoning. Our implemented system, called CABINS, records situation-dependent tradeoffs and consequences that result from schedule revision to guide schedule improvement. The preliminary experimental results show that CABINS is able to effectively capture both user static and dynamic preferences which are not known to the system and only exist implicitly in a extensional manner in the case base.

Connected through hyperedge HE-1 (induced by source paper "Using Case-Based Reasoning as a Reinforcement Learning Framework for Optimization with Changing Criteria"):
  with members:
    - "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,"
    - "Transfer of Learning by Composing Solutions of Elemental Sequential Tasks"
    - "Case-based Acquisition of User Preferences for Solution Improvement in Ill-Structured Domains"

Connected through hyperedge HE-2 (induced by source paper "Case-based Acquisition of User Preferences for Solution Improvement in Ill-Structured Domains"):
  with members:
    - "Improving accuracy by combining rule-based and case-based reasoning"
    - "Using Case-Based Reasoning as a Reinforcement Learning Framework for Optimization with Changing Criteria"
    - "Modeling Ill-Structured Optimization Tasks through Cases"

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