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: "Supporting Combined Human and Machine Planning: The Prodigy 4.0 User Interface Version 2.0*"
  Abstract: Realistic and complex planning situations require a mixed-initiative planning framework in which human and automated planners interact to mutually construct a desired plan. Ideally, this joint cooperation has the potential of achieving better plans than either the human or the machine can create alone. Human planners often take a case-based approach to planning, relying on their past experience and planning by retrieving and adapting past planning cases. Planning by analogical reasoning in which generative and case-based planning are combined, as in Prodigy/Analogy, provides a suitable framework to study this mixed-initiative integration. However, having a human user engaged in this planning loop creates a variety of new research questions. The challenges we found creating a mixed-initiative planning system fall into three categories: planning paradigms differ in human and machine planning; visualization of the plan and planning process is a complex, but necessary task; and human users range across a spectrum of experience, both with respect to the planning domain and the underlying planning technology. This paper presents our approach to these three problems when designing an interface to incorporate a human into the process of planning by analogical reasoning with Prodigy/Analogy. The interface allows the user to follow both generative and case-based planning, it supports visualization of both plan and the planning rationale, and it addresses the variance in the experience of the user by allowing the user to control the presentation of information. * This research is sponsored as part of the DARPA/RL Knowledge Based Planning and Scheduling Initiative under grant number F30602-95-1-0018. A short version of this document appeared as Cox, M. T., & Veloso, M. M. (1997). Supporting combined human and machine planning: An interface for planning by analogical reasoning. In D. B. Leake & E. Plaza (Eds.), Case-Based Reasoning Research and Development: Second International Conference on Case-Based Reasoning (pp. 531-540). Berlin: Springer-Verlag.

Connected through hyperedge HE-1 (induced by source paper "Merge Strategies for Multiple Case Plan Replay"):
  with members:
    - "Evaluating the Effectiveness of Derivation Replay in Partial-order vs State-space Planning"
    - "Supporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning"

Connected through hyperedge HE-2 (induced by source paper "Towards Mixed-Initiative Rationale-Supported Planning"):
  with members:
    - "Supporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning"

Connected through hyperedge HE-3 (induced by source paper "Supporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning"):
  with members:
    - "S o l u t i o n Relevant A b s t r a"
    - "Learning to Improve Case Adaptation by Introspective Reasoning and CBR"
    - "Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning"
    - "On the Usefulness of Re-using Diagnostic Solutions"
    - "A Case Study of Case-Based CBR"
    - "Merge Strategies for Multiple Case Plan Replay"
    - "Towards Mixed-Initiative Rationale-Supported Planning"

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