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Abstract

This paper addresses Narrative Intelligence from a bottom up, Artificial Life perspective. First, different levels of narrative intelligence are discussed 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 described which is applied to the study of story-telling, using robotic agents as examples of situated, autonomous minimal agents. Experimental data are provided which support the working hypothesis that story-telling can be advantageous, i.e. increases the survival of an autonomous, autobiographic, minimal agent. We conclude this paper by discussing implications of this approach for story-telling in humans and artifacts.

@article{dautenhahn01narrativeIntelligence,
  author={Kerstin Dautenhahn and Steven J. Coles},
  title={Narrative Intelligence from the Bottom Up: A Computational Framework for the Study of Story-Telling in Autonomous Agents},
  journal={Journal of Artificial Societies and Social Simulation},
  year={2001},
  volume={4},
  number={1},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/dautenhahn01narrativeIntelligence.html}
}