Connectionist modelling of skill dynamics

This paper discusses a method for modelling skilled action for synthetic actors in a virtual environment. The method guides lower‐level motor skills from a connectionist model of skill memory, implemented as collections of trained neural networks. The relationship between this work and that of other projects in task‐level animation is discussed, the principles of connectionist learning are explained, and a series of experiments testing the concept of connectionist skill modelling are reviewed.