Partial Plan Recognition Using Predictive Agents

  • Jung-Jin Lee
  • Robert McCartney
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1599)

Abstract

This work explores the benefits of using user models for plan recognition problems in a real-world application. Interface agents are designed for the prediction of resource usage in the UNIX domain using a stochastic approach to automatically acquire regularities of user behavior. Both sequential information from the command sequence and relational information such as system’s responses and arguments to the commands are considered to typify a user’s behavior and intentions. Issues of ambiguity, distraction and interleaved execution of user behavior are examined and taken into account to improve the probability estimation in hidden Markov models. This paper mainly represents both ideal and simplified models to represent and solve the prediction problem on a theory basis.

Keywords

Hide Markov Model Multiagent System User Behavior Interface Agent Plan Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Jung-Jin Lee
    • 1
  • Robert McCartney
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of ConnecticutStorrsUSA

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