Modeling sensation for an intelligent virtual agent's perception process
Perception is an important aspect of cognition since it forms the basis for further decision-making processes. In this contribution, the overall architecture of our synthetic perception for agents framework (SynPeA) for simulating a virtual entities perception is presented. We discuss aspects of modeling visual sensation and propose mechanisms for virtual sensors and memory. Different visual sensing approaches are compared by applying them to an artificial evaluation scenario. The evaluations show promising results with respect to performance and quality.