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: "Plausibility Measures and Default Reasoning"
  Abstract: We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility measures. We focus on one application of plausibility measures in this paper: default reasoning. In recent years, a number of different semantics for defaults have been proposed, such as preferential structures, *-semantics, possibilistic structures, and -rankings, that have been shown to be characterized by the same set of axioms, known as the KLM properties. While this was viewed as a surprise, we show here that it is almost inevitable. In the framework of plausibility measures, we can give a necessary condition for the KLM axioms to be sound, and an additional condition necessary and sufficient to ensure that the KLM axioms are complete. This additional condition is so weak that it is almost always met whenever the axioms are sound. In particular, it is easily seen to hold for all the proposals made in the literature.

Connected through hyperedge HE-1 (induced by source paper "On the Complexity of Conditional Logics"):
  with members:
    - "Updates and Counterfactuals"
    - "A Knowledge-Based Framework for Belief Change Part I: Foundations"
    - "Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions."
    - "Defining Relative Likelihood in Partially-Ordered Preferential Structures"

Connected through hyperedge HE-2 (induced by source paper "Plausibility Measures: A User's Guide"):
  with members:
    - "Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions."
    - "A Qualitative Markov Assumption and Its Implications for Belief Change"

Connected through hyperedge HE-3 (induced by source paper "A Qualitative Markov Assumption and Its Implications for Belief Change"):
  with members:
    - "Generalized Update: Belief Change in Dynamic Settings"
    - "A Knowledge-Based Framework for Belief Change Part I: Foundations"
    - "Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions."
    - "Modeling Belief in Dynamic Systems. Part I: Foundations"
    - "Plausibility Measures: A User's Guide"

Connected through hyperedge HE-4 (induced by source paper "Defining Relative Likelihood in Partially-Ordered Preferential Structures"):
  with members:
    - "On the Complexity of Conditional Logics"
    - "Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions."

Connected through hyperedge HE-5 (induced by source paper "Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions."):
  with members:
    - "On the Complexity of Conditional Logics"
    - "Generalized Update: Belief Change in Dynamic Settings"
    - "A Knowledge-Based Framework for Belief Change Part I: Foundations"
    - "Abduction as Belief Revision"
    - "Abduction to Plausible Causes: An Event-based Model of Belief Update"
    - "A Qualitative Markov Assumption and Its Implications for Belief Change"
    - "Plausibility Measures: A User's Guide"
    - "Defining Relative Likelihood in Partially-Ordered Preferential Structures"

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