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 "Probabilistic evaluation of sequential plans from causal models with hidden variables"):
  Abstract: The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a given plan can be predicted from passive observations on measured variables only. When the criterion is satisfied, a closed-form expression is provided for the probability that the plan will achieve a specified goal.

Includes members:
  Member "The New Challenge: From a Century of Statistics to an Age of Causation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Causal diagrams for empirical research")
  Member "Causal diagrams for empirical research":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Causal Inference from Indirect Experiments")
  Member "Axioms of Causal Relevance":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "On the Testability of Causal Models with Latent and Instrumental Variables")
  Member "A Probabilistic Calculus of Actions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Counterfactuals and Policy Analysis in Structural Models")
  Member "On the Testability of Causal Models with Latent and Instrumental Variables":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Causal diagrams for empirical research")

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: Probabilistic_Methods