An exploratory model of remembering, telling and understanding experience in simple agents

Given the importance of narrative for the way humans perceive the world and exchange information about it, it is surprising how little we know about the procedures by which reality is represented as narrative. This is in part due to the well known fact that humans are bad at being aware of their own though processes. It is also influenced by the fact that the ability to generate and process narratives is so pervasive that everybody takes it for granted. Although this is not a worrying issue in general terms, it is a significant problem for recent efforts to construct computational models of this narrative ability. The present paper describes an elementary computational model of a society of agents driven by a need for information, where the ability to represent and communicate reality as a sequential stream of symbols can be shown to provide advantages in terms of maximising the amount of information compiled by a given agent over a given period. This model is not intended as a plausible model of human cognition. The human narrative ability has broader range and significantly higher complexity. However, the model is phrased in terms of elementary principles that can also be seen to underlie more complex models. The paper discusses consequences and insights arising from this model that may be relevant for wider consideration of narrative.