human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Dynamic Constraint Satisfaction using Case-Based Reasoning Techniques"):
  Abstract: The Dynamic Constraint Satisfaction Problem (DCSP) formalism has been gaining attention as a valuable and often necessary extension of the static CSP framework. Dynamic Constraint Satisfaction enables CSP techniques to be applied more extensively, since it can be applied in domains where the set of constraints and variables involved in the problem evolves with time. At the same time, the Case-Based Reasoning (CBR) community has been working on techniques by which to reuse existing solutions when solving new problems. We have observed that dynamic constraint satisfaction matches very closely the case-based reasoning process of case adaptation. These observations emerged from our previous work on combining CBR and CSP to achieve a constraint-based adaptation. This paper summarizes our previous results, describes the similarity of the challenges facing both DCSP and case adaptation, and shows how CSP and CBR can together begin to address these chal lenges.

Includes members:
  Member "Towards Improving Case Adaptability with a Genetic Algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Synergy and Commonality in Case-Based and Constraint-Based Reasoning")
  Member "Towards A Computer Model of Memory Search Strategy Learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Goal-Driven Learning: Fundamental Issues (A Symposium Report)")
  Member "Synergy and Commonality in Case-Based and Constraint-Based Reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Towards Improving Case Adaptability with a Genetic Algorithm")
  Member "A CBR Integration From Inception to Productization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Towards Improving Case Adaptability with a Genetic Algorithm")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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