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 "MULTISTRATEGY LEARNING IN REACTIVE CONTROL SYSTEMS FOR AUTONOMOUS ROBOTIC NAVIGATION"):
  Abstract: This paper presents a self-improving reactive control system for autonomous robotic navigation. The navigation module uses a schema-based reactive control system to perform the navigation task. The learning module combines case-based reasoning and reinforcement learning to continuously tune the navigation system through experience. The case-based reasoning component perceives and characterizes the system's environment, retrieves an appropriate case, and uses the recommendations of the case to tune the parameters of the reactive control system. The reinforcement learning component refines the content of the cases based on the current experience. Together, the learning components perform on-line adaptation, resulting in improved performance as the reactive control system tunes itself to the environment, as well as on-line case learning, resulting in an improved library of cases that capture environmental regularities necessary to perform on-line adaptation. The system is extensively evaluated through simulation studies using several performance metrics and system configurations.

Includes members:
  Member "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Clay: Integrating Motor Schemas and Reinforcement Learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Learning Roles: Behavioral Diversity in Robot Teams")
  Member "Systematic Evaluation of Design Decisions in CBR Systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Structure oriented case retrieval")
  Member "Continuous Case-Based Reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Systematic Evaluation of Design Decisions in CBR Systems")
  Member "Knowledge Compilation and Speedup Learning in Continuous Task Domains":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Case-based reactive navigation: A case-based method for on-line selection and adaptation of reactive control parameters")
  Member "A Case-Based Approach to Reactive Control for Autonomous Robots":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Using Case-Based Reasoning for Mobile Robot Navigation")
  Member "Case-based reactive navigation: A case-based method for on-line selection and adaptation of reactive control parameters":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "Knowledge Compilation and Speedup Learning in Continuous Task Domains")

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