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The results of optimal control theory applied to deterministic fishery models is extended to the continuous stochastic case. The simple logistic model is generalized to stochastic models by singly considering the logistic parameters and the fishing harvest as random processes. Approximate probability density functions are calculated for one model. The stochastic models are applied to the Atlantic sea-scallop fishery. Dynamic programming is used to obtain control solutions.