1. A method for training a system to identify state changes in objects in virtual worlds, the method comprising: observing a group of one or more base events, wherein each base event includes a state change in an object in a virtual world; determining by a computer processor that the group of one or more of the observed base events is correlated to a candidate higher-level event, the candidate higher-level event including at least some of the observed base events, wherein determining that the group of one or more of the observed base events is correlated to the candidate higher-level event is based at least in part on statistical analysis of the observed base events; receiving user input confirming that the group of base events is correlated to the candidate higher-level event; if the received user input specifies that the group of base events is correlated to the candidate higher-level, storing the candidate higher-level event as an identified higher-level event; and abstracting the identified higher-level event to another identified higher-level event, such that the another identified higher-level event includes a plurality of events similar to the identified higher level event but having a different identity than the identified higher-level event.