Our work links Chinese calligraphy to computer science through an integrated intelligence approach. We first extract strokes of existent calligraphy using a semi-automatic, two-phase mechanism: the first phase tries to do the best possible extraction using a combination of algorithmic techniques; the second phase presents an intelligent user interface to allow the user to provide input to the extraction process for the difficult cases such as those in highly random, cursive, or distorted styles. Having derived a parametric representation of calligraphy, we employ a supervised learning based method to explore the space of visually pleasing calligraphy. A numeric grading method for judging the beauty of calligraphy is then applied to the space. We integrate such a grading unit into an existent constraint-based reasoning system for calligraphy generation, which results in a significant enhancement in terms of visual quality in the automatically generated calligraphic characters. Finally, we construct an intelligent calligraphy tutoring system making use of the above. This work represents our first step towards understanding the human process of appreciating beauty through modeling the process with an integration of available AI techniques. More results and supplementary materials are provided at http://www.cs.hku.hk/~songhua/calligraphy.