Autonomous Virtual Agents Learning a Cognitive Model and Evolving

摘要

In this paper, we propose a new integration approach to simulate an Autonomous Virtual Agent's cognitive learning of a task for interactive Virtual Environment applications. Our research focuses on the behavioural animation of virtual humans capable of acting independently. Our contribution is important because we present a solution for fast learning with evolution. We propose the concept of a Learning Unit Architecture that functions as a control unit of the Autonomous Virtual Agent's brain. Although our technique has proved to be effective in our case study, there is no guarantee that it will work for every imaginable Autonomous Virtual Agent and Virtual Environment. The results are illustrated in a domain that requires effective coordination of behaviours, such as driving a car inside a virtual city.