Narrative intelligence from the bottom up: A computational framework for the study of story-telling in autonomous agents

This paper addresses Narrative Intelligence from a bottom up, Artificial Li fe perspective. First, different levels of narrative intelligence are discu ssed in the context of human and robotic story-tellers. Then, we introduce a computational framework which is based on minimal definitions of stories, story-telling and autobiographic agents. An experimental test-bed is descr ibed which is applied to the study of story-telling, using robotic agents a s examples of situated, autonomous minimal agents. Experimental data are pr ovided which support the working hypothesis that story-telling can be advan tageous, i.e. increases the survival of an autonomous, autobiographic, mini mal agent. We conclude this paper by discussing implications of this approa ch for story-telling in humans and artifacts.