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 "Systematic Evaluation of Design Decisions in CBR Systems"):
  Abstract: Two important goals in the evaluation of an AI theory or model are to assess the merit of the design decisions in the performance of an implemented computer system and to analyze the impact in the performance when the system faces problem domains with different characteristics. This is particularly difficult in case-based reasoning systems because such systems are typically very complex, as are the tasks and domains in which they operate. We present a methodology for the evaluation of case-based reasoning systems through systematic empirical experimentation over a range of system configurations and environmental conditions, coupled with rigorous statistical analysis of the results of the experiments. This methodology enables us to understand the behavior of the system in terms of the theory and design of the computational model, to select the best system configuration for a given domain, and to predict how the system will behave in response to changing domain and problem characteristics. A case study of a mul-tistrategy case-based and reinforcement learning system which performs autonomous robotic navigation is presented as an example.

Includes members:
  Member "MULTISTRATEGY LEARNING IN REACTIVE CONTROL SYSTEMS FOR AUTONOMOUS ROBOTIC NAVIGATION":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming")
  Member "Generalizing from Case Studies: A Case Study":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms")
  Member "Structure oriented case retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Towards Formalizations in Case-Based Reasoning for Synthesis")
  Member "Continuous Case-Based Reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "MULTISTRATEGY LEARNING IN REACTIVE CONTROL SYSTEMS FOR AUTONOMOUS ROBOTIC NAVIGATION")

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