Skip to main content
Article thumbnail
Location of Repository

Logic-based plan recognition for intelligent help systems

By Mathias Bauer and Gabriele Paul

Abstract

Intelligent help systems aim at providing optimal help to the users of complex software application systems. In this context plan recognition is essential for a cooperative system behavior in that it allows to predict the user\u27s future actions, to determine suboptimal action sequences or even serves as a basis for user-adapted tutoring or learning components. In this paper a new approach to incremental plan recognition based on a modal temporal logic is described. This logic allows for an abstract representation of plans including control structures such as loops and conditionals which makes it particularly well-suited for the above-mentioned tasks in command-language environments. There are two distinct phases: With a generalized abductive reasoning mechanism the set of valid plan hypotheses is determined in each recognition step. A probabilistic selection, based on Dempster-Shafer Theory, then serves to determine the "best" hypotheses in order to be able to provide help whenever required

Topics: Künstliche Intelligenz, Data processing Computer science
Publisher: Sonstige Einrichtungen. DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Year: 1993
OAI identifier: oai:scidok.sulb.uni-saarland.de:3706

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.