TR2000-36

Learning Task Models for Collagen (subsumed by TR2002-04)

    •  Andrew Garland, Charles Rich, Candace Sidner, Neal Lesh, "Learning Task Models for Collagen (subsumed by TR2002-04)", Tech. Rep. TR2000-36, Mitsubishi Electric Research Laboratories, Cambridge, MA, September 2000.
      BibTeX TR2000-36 PDF
      • @techreport{MERL_TR2000-36,
      • author = {Andrew Garland, Charles Rich, Candace Sidner, Neal Lesh},
      • title = {Learning Task Models for Collagen (subsumed by TR2002-04)},
      • institution = {MERL - Mitsubishi Electric Research Laboratories},
      • address = {Cambridge, MA 02139},
      • number = {TR2000-36},
      • month = sep,
      • year = 2000,
      • url = {https://www.merl.com/publications/TR2000-36/}
      • }
  • Research Areas:

    Artificial Intelligence, Data Analytics

Abstract:

For an application-independent collaborative tool, a key step is to develop a detailed task model for a particular domain. This is a time consuming and difficult task, and seems to require a fairly advanced knowledge of AI representations for plans, goals, and recipes. This paper discusses some preliminary ideas for making it easier to construct and evolve task models, either through interaction with a human domain expert, through machine learning, or in a mixed-initiative system.