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: "editors. Representing Preferences as Ceteris Paribus Comparatives"
  Abstract: Decision-theoretic preferences specify the relative desirability of all possible outcomes of alternative plans. In order to express general patterns of preference holding in a domain, we require a language that can refer directly to preferences over classes of outcomes as well as individuals. We present the basic concepts of a theory of meaning for such generic compar-atives to facilitate their incremental capture and exploitation in automated reasoning systems. Our semantics lifts comparisons of individuals to comparisons of classes "other things being equal" by means of contextual equivalences, equivalence relations among individuals that vary with the context of application. We discuss implications of the theory for represent ing preference information.

Connected through hyperedge HE-1 (induced by source paper "Toward Rational Planning and Replanning Rational Reason Maintenance, Reasoning Economies, and Qualitative Preferences formal notions"):
  with members:
    - "Rational Belief Revision (Preliminary Report)"
    - "Rationality and its Roles in Reasoning"

Connected through hyperedge HE-2 (induced by source paper "Some recent ideas on utility (and probability) (not for distribution or reference)"):
  with members:
    (none)

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