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Narrative Intelligence from the Bottom Up: a Computational Framework for the Study of Story-Telling in Autonomous Agents

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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.

Suggested Citation

  • Kerstin Dautenhahn & Steve Coles, 2001. "Narrative Intelligence from the Bottom Up: a Computational Framework for the Study of Story-Telling in Autonomous Agents," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(1), pages 1-1.
  • Handle: RePEc:jas:jasssj:2000-9-1
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