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A computational framework is presented which is used to model the process by which human language learners acquire the syntactic component of their native language. The focus is feasibility - is acquisition possible within a reasonable amount of time and/or with a reasonable amount of work? The approach abstracts away from specific linguistic descriptions in order to make a `broad-stroke' prediction of an acquisition model's behavior by formalizing factors that contribute to cross-linguistic ambiguity. Discussion centers around an application to Fodor's Structural Trigger's Learner (STL) (1998) and concludes with the proposal that successful computational modeling requires a parallel psycholinguistic investigation of the distribution of ambiguity across the domain of human languages.