1. A method of storing and using a set of observations of real-world events and actions, the method comprising: generating clusters based on the set of observations, each cluster representing correlations between events and actions in a subset of the observations in the set of observations; processing the clusters into a first linked graph based on a set of rules to identify correlations between the events and actions in the set of the observations, the first linked graph tagged to indicate the correlations between the events and the actions based on the set of rules; presupposing that an event is reversible unless an observation contradicting reversibility of the event is obtained; and tagging an edge associated with the irreversible event as having uncertain correlations with actions that are irreversible.
1. A method of storing and using a set of observations of real-world events and actions, the method comprising: generating clusters based on the set of observations, each cluster representing correlations between events and actions in a subset of the observations in the set of observations; processing the clusters into a first linked graph based on a set of rules to identify correlations between the events and actions in the set of the observations, the first linked graph tagged to indicate the correlations between the events and the actions based on the set of rules; presupposing that an event is reversible unless an observation contradicting reversibility of the event is obtained; and tagging an edge associated with the irreversible event as having uncertain correlations with actions that are irreversible. 5. The method of claim 1 , wherein each cluster comprises a decision point representing a state where an action can be started, and processing the clusters comprises merging two or more decision points of two or more clusters into one decision point to resolve inconsistencies in the two or more clusters.