Publication year: 2011 Source: Artificial Intelligence, Available online 3 October 2011 Gal Yaʼakov, Swapna Reddy, Stuart Shieber, Andee Rubin, Barbara Grosz This paper describes a challenging plan recognition problem that arises in environments in which agents engage widely in exploratory behavior, and presents new algorithms for effective plan recognition in such settings. In exploratory domains, agentsʼ actions map onto logs of behavior that include switching between activities, extraneous actions, and mistakes. Flexible pedagogical software, such as the application considered in this paper for statistics education, is a paradigmatic example of such domains, but many other settings exhibit similar characteristics.
Excerpt from:
Plan recognition in exploratory domains