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|Title: ||A Reinforcement Learning Approach to Determine Horizontal Spaces in Typefaces|
|Authors: ||Ranathunga, N.M|
|Issue Date: ||2017|
Typeface spacing is a hard problem. It takes countless hours of manual labour to achieve
an aesthetically pleasing font, one frequently encounters in digital media. The amount of
space between two letters (inter-letter space) significantly contributes to the aesthetically
pleasing nature and readability of the typeface. Although inter-letter spacing defines the
texture and feel of a typeface and when done accurately yields aesthetically balanced, and
an appealing typeface. Setting spacing in a typeface is a tedious and time-consuming task.
Hence this research presents an exploratory study investigating potential of reinforcement
learning models to fully automate the typeface spacing process.
The proposed reinforcement learning model, first of it’s kind was able to achieve good
accuracies even with a simple reward function. Some of the visual differences were subtle.
Thus, we conclude that reinforcement learning models can indeed be used to model the
typeface spacing problem and as one of the first attempts to apply reinforcement learning
models in this particular problem domain, this study lays the foundation to future research
|Appears in Collections:||SCS Individual/Group Project - Final Thesis (2017)|
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