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: "Heuristics and Normative Models of Judgment under Uncertainty"
  Abstract: Psychological evidence shows that probability theory is not a proper descriptive model of intuitive human judgment. Instead, some heuristics have been proposed as such a descriptive model. This paper argues that probability theory has limi tations even as a normative model. A new normative model of judgment under uncertainty is designed under the assumption that the system's knowledge and resources are insufficient with respect to the questions that the system needs to answer. The proposed heuristics in human reasoning can also be observed in this new model, and can be justified according to the assumption.

Connected through hyperedge HE-1 (induced by source paper "Belief Revision in Probability Theory"):
  with members:
    - "Confidence as Higher Order Uncertainty proposed for handling higher order uncertainty, including the Bayesian approach,"
    - "From Inheritance Relation to Non-Axiomatic Logic"
    - "A Unified Treatment of Uncertainties"
    - "Reference Classes and Multiple Inheritances"
    - "A Defect in Dempster-Shafer Theory"

Connected through hyperedge HE-2 (induced by source paper "From Inheritance Relation to Non-Axiomatic Logic"):
  with members:
    - "Confidence as Higher Order Uncertainty proposed for handling higher order uncertainty, including the Bayesian approach,"
    - "Belief Revision in Probability Theory"
    - "Non-Axiomatic Reasoning System (Version 2.2) used to show how the system works. The limitations of"
    - "A Unified Treatment of Uncertainties"
    - "Reference Classes and Multiple Inheritances"
    - "A Defect in Dempster-Shafer Theory"
    - "A New Approach for Induction: From a Non-Axiomatic Logical Point of View"

Connected through hyperedge HE-3 (induced by source paper "Non-Axiomatic Reasoning System (Version 2.2) used to show how the system works. The limitations of"):
  with members:
    - "Confidence as Higher Order Uncertainty proposed for handling higher order uncertainty, including the Bayesian approach,"
    - "From Inheritance Relation to Non-Axiomatic Logic"
    - "A Unified Treatment of Uncertainties"
    - "Reference Classes and Multiple Inheritances"
    - "A Defect in Dempster-Shafer Theory"
    - "A New Approach for Induction: From a Non-Axiomatic Logical Point of View"

Connected through hyperedge HE-4 (induced by source paper "Reference Classes and Multiple Inheritances"):
  with members:
    - "Belief Revision in Probability Theory"
    - "From Inheritance Relation to Non-Axiomatic Logic"
    - "Non-Axiomatic Reasoning System (Version 2.2) used to show how the system works. The limitations of"
    - "A New Approach for Induction: From a Non-Axiomatic Logical Point of View"

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: Probabilistic_Methods