1. A method of updating at least one prediction model for use by at least one interactive server, wherein each interactive server is configured to perform a plurality of actions in the context of a plurality of input attribute values and wherein the actions are selected based on each prediction model, the method comprising: (a) automatically and continually obtaining contextual data from the interactive server as it performs the plurality of actions, wherein the contextual data indicates at least which action was performed, which input attribute values are present for each action that was performed, and which outcome is achieved for each action was performed; (b) automatically and continually updating a learning model based on all of the obtained contextual data, wherein the learning model is configured to predict a probability of each of a plurality of specific outcomes occurring for each of a plurality of specific actions being performed by the interactive server when specific combinations of one or more input attribute values are present; and (c) automatically and continually pruning one or more values of such input attributes from the learning model to thereby update a prediction model that is usable by the interactive server, whereby the pruning is accomplished so that input attributes values which do not significantly affect the outcomes of the actions being performed are eliminated from being used by the prediction model to predict the plurality of probabilities.