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Autonomous Agents as Competent Assistants : Better Interpretation of Pen Gestures

Interaction between users and synthetic hardware systems have provided opportunities to utilise an important sensing modality through the use of a digital pen (stylus). Ambient learning environments insist on recognising and reacting to users’ input sketches and gestures for expediting the responses needed to improve user-interface (UI) supports for more natural communications. This paper focuses on the techniques and methodologies used in ciphering information obtained from digital ink compositions that gave way to the conceptions of elaborate and intelligent programs. We present our classification of sketch-objects for identification purposes while maintaining their native attributes, and discuss our approaches for interpreting them as valid intended gestures through autonomous agents.