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From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, Flexibly Instructable Agents  ...
Message-ID: <1995Nov28.235814.16406@ptolemy-ethernet.arc.nasa.gov>
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Date: Tue, 28 Nov 1995 23:58:14 GMT
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JAIR is pleased to announce the publication of the following article:

Huffman, S.B. and Laird, J.E. (1995)
  "Flexibly Instructable Agents", Volume 3, pages 271-324.
   PostScript: volume3/huffman95a.ps (1599K)
	       compressed, volume3/huffman95a.ps.Z (476K)


   Abstract: This paper presents an approach to learning from situated,
   interactive tutorial instruction within an ongoing agent.  Tutorial
   instruction is a flexible (and thus powerful) paradigm for teaching
   tasks because it allows an instructor to communicate whatever types of
   knowledge an agent might need in whatever situations might arise.  To
   support this flexibility, however, the agent must be able to learn
   multiple kinds of knowledge from a broad range of instructional
   interactions.  Our approach, called situated explanation, achieves
   such learning through a combination of analytic and inductive
   techniques.  It combines a form of explanation-based learning that is
   situated for each instruction with a full suite of contextually guided
   responses to incomplete explanations.  The approach is implemented in
   an agent called Instructo-Soar that learns hierarchies of new tasks
   and other domain knowledge from interactive natural language
   instructions.  Instructo-Soar meets three key requirements of flexible
   instructability that distinguish it from previous systems: (1) it can
   take known or unknown commands at any instruction point; (2) it can
   handle instructions that apply to either its current situation or to a
   hypothetical situation specified in language (as in, for instance,
   conditional instructions); and (3) it can learn, from instructions,
   each class of knowledge it uses to perform tasks.

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