A neurobiologically inspired model of personality in an intelligent agent

  • Authors:
  • Stephen Read;Lynn Miller;Brian Monroe;Aaron Brownstein;Wayne Zachary;Jean-Christophe LeMentec;Vassil Iordanov

  • Affiliations:
  • Department of Psychology, University of Southern California, Los Angeles, California;Annenberg School for Communication, University of Southern California, Los Angeles, CA;Department of Psychology, University of Southern California, Los Angeles, California;Department of Psychology, University of Southern California, Los Angeles, California;CHI Systems, Inc., Ft. Washington, PA;CHI Systems, Inc., Ft. Washington, PA;CHI Systems, Inc., Ft. Washington, PA

  • Venue:
  • IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
  • Year:
  • 2006

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Abstract

We demonstrate how current knowledge about the neurobiology and structure of human personality can be used as the basis for a computational model of personality in intelligent agents (PAC—personality, affect, and culture). The model integrates what is known about the neurobiology of human motivation and personality with knowledge about the psy chometric structure of trait language and personality tests. Thus, the current model provides a principled theoretical account that is based on what is currently known about the structure and neurobiology of human personality and tightly integrates it into a computational architecture. The result is a motive-based computational model of personality that provides a psychologically principled basis for intelligent virtual agents with realistic and engag ing personality.