Autonomous virtual agents learning a cognitive model and evolving

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

Published in:
Proceedings, IVA 2005.
Presented at:
5th International Working Conference, IVA 2005., Kos, Greece, 2005
Virtual Reality Lab, Ecole Polytechnique Federale de Lausanne, Switzerland
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 Record created 2007-01-16, last modified 2018-03-17

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