Because we as readers share a lot of the same scripts, it is not necessary to repeat all the events every time a script occurs. They can be filled in automatically, and the actual text of the story can concentrate on the interesting parts. To understand how people process stories, we have to understand how they learn and use script-based knowledge. There is a good amount of psychological evidence on script processing. The view of scripts as rather rigid chains of events, however, is an artifact of the symbolic implementation and does not seem to match psychological reality.
People form new scripts all the time, based on regularities in experience.
Any number of co-occurring events can form a script, and their associations can be of varying strengths. It turns out that this more general view of scripts as regularities in experience is consistent with the neural network approach, and much more natural to implement than scripts as rigid causal chains. How to extend the subsymbolic approach beyond scripts is currently an open question. It seems that simple pattern transformation mechanisms that work so well with scripts may not be extensible to processing deviations and other less regular information. Subsymbolic Processing of Embedded Structures.