Abstract: In this talk I am going to describe some work done to investigate the process of grammatical acquisition from data. The computational learning system used is composed of a Universal Grammar with associated parameters, and a learning algorithm, following the Principles and Parameters Theory. The learning algorithm receives input from a corpus of child-directed speech annotated with logical forms and sets the parameters based on this input. This framework is used as basis to investigate several aspects of language acquisition. In this talk I am going to describe the components of the learning system and some experiments performed. The results obtained in these experiments show a convergence towards the target grammar given the input data available, and that this is possible even in the face of ambiguous and noisy input data.