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Please predict whether this patent is acceptable.PATENT ABSTRACT: Discovery of causal models via experimentation is essential in numerous applications fields. One of the primary objectives of the invention is to minimize the use of costly experimental resources while achieving high discovery accuracy. The invention provides new methods and processes to enable accurate discovery of local causal pathways by integrating high-throughput observational data with efficient experimentation strategies. At the core of these methods are computational causal discovery techniques that account for multiplicity (i.e., indistinguishability) of causal pathways consistent with observational data. The invention, when applied for discovery of local causal pathways from a combination of observational and experimental data, achieves higher discovery accuracy than existing observational approaches and uses fewer experimental resources than existing experimental approaches. Repeated application of the invention for each variable in the modeled system produces the full causal model.