Abstract
Believable interactions between synthetic characters are an important factor defining the success of a game relying on the player being able to create emotional bonds with the game characters. As important as the character being themselves believable is that the interaction with or between such characters is believable. Although research in synthetic characters has developed several models to improve character believability, interactions are generally not the focus of such works. This may be one of the reasons why state of the art models from Academia are still not being used in commercial products. In this thesis, we bridged affective computing and traditional animation principles and create a model for character interaction based on anticipation and emotion that allows for precise affective communication of intention-based behaviors. We also present a study with 52 subjects supporting that our proposal is able to increase scene believability when compared to traditional approaches.