The RADAR architecture for personal cognitive assistance

Current desktop environments provide weak support for carrying out complex user-oriented tasks. Although individual applications are becoming increasingly sophisticated and feature-rich, users must map their high-level goals to the low-level operational vocabulary of applications, and deal with a myriad of routine tasks (such as keeping up with email, keeping calendars and web sites up-to-date, etc.). An alternative vision is that of a personal cognitive assistant. Like a good secretary, such an assistant would help users accomplish their high-level goals, coordinating the use of multi-ple applications, automatically handling routine tasks, and, most importantly, adapting to the indi-vidual needs of a user over time. In this paper we describe the architecture and its implementation for a personal cognitive assistant called RADAR. Key features include (a) extensibility through the use of a plug-in agent architecture (b) transparent integration with legacy applications and data of today’s desktop environments, and (c) extensive use of learning so that the environment adapts to th