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: "Explaining "Explaining Away""
  Abstract: Explaining away is a common pattern of reasoning in which the confirmation of one cause of an observed or believed event reduces the need to invoke alternative causes. The opposite of explaining away also can occur, in which the confirmation of one cause increases belief in another. We provide a general qualitative probabilistic analysis of intercausal reasoning, and identify the property of the interaction among the causes, product synergy, that determines which form of reasoning is appropriate. Product synergy extends the qualitative probabilistic network (QPN) formalism to support qualitative intercausal inference about the directions of change in probabilistic belief. The intercausal relation also justifies Occam's razor, facilitating pruning in search for likely diagnoses. 0 Portions of this paper originally appeared in Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning [16]. y Supported by the National Science Foundation under grant IRI-8807061 to Carnegie Mellon and by the Rockwell International Science Center.

Connected through hyperedge HE-1 (induced by source paper "Inference in Cognitive Maps"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Some Varieties of Qualitative Probability"):
  with members:
    - "Incremental Tradeoff Resolution in Qualitative Probabilistic Networks"

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