Trees? Last time I studied AI we used probabilistic networks, AKA belief networks. That is, a node for each random variable, an edge for each non-indipendent pair of nodes, and a table of joined probability distribution for each edge.
Or, you may be talking about decision trees with stochastic discriminators...
In both cases, I'd use a standard algorithm on an in-memory representation, and then (when needed) serialize that representation as XML on filesystem or database.
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dakkar - Mobilis in mobile
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