"510","Modelling Learning as Modelling","Economists tend to represent learning as a procedure for estimating the parameters of the \"correct\" econometric model. We extend this approach by assuming that agents specify as well as estimate models. Learning thus takes the form of a dynamic process of developing models using an internal language of representation where expectations are formed by forecasting with the best current model. This introduces a distinction between the form and content of the internal models which is particularly relevant for boundedly rational agents. We propose a framework for such model development which use a combination of measures: the error with respect to past data, the complexity of the model, the cost of finding the model and a measure of the model's specificity The agent has to make various trade-offs between them. A utility learning agent is given as an example.","http://cogprints.org/510/","Moss, Scott and Edmonds, Bruce","UNSPECIFIED"," Moss, Scott and Edmonds, Bruce (1994) *Modelling Learning as Modelling.* [Journal (Paginated)] ","","1994-11"