Abstract
A major research problem regarding believable agents is how to develop and execute their behavioral libraries. This work identifies two different approaches: the ‘author‐based’ one, depending on the designer's ability to hand‐code each agent's behavioral features, and the ‘model‐based’ one, grounded on a model which, starting from a set of primitives provided by the designer, automatically generates the agents' typical actions. This paper proposes to integrate the two methods by means of a two‐phase/two‐step strategy, that partially relieves the designer of the burden of hand‐coding all the behavioral libraries, while still allowing a good control over the characters' performance, and enabling the runtime creation and storage of new behaviors. A case study concretely illustrates how such strategy is implemented by means of a hybrid planning architecture, coupled with a goal‐based model of personality, in order to realize characters that interact with the user according to their personalities.
Get full access to this article
View all access options for this article.