Techniques for Modeling Human Performance in Synthetic Environments: A Supplementary Review

摘要

Selected recent developments and promising directions for improving the quality of models of human performance in synthetic environments are summarized, beginning with the potential uses and goals for behavioral models. The focus is on providing more complete performance, better integration of the models with synthetic environments and with each other (reusability), and improved usability of the models. Within this context, relevant, current work related to modeling is reviewed, such as cognitive modeling of emotion, advanced techniques for testing and building models of behavior, new cognitive architectures including hybrid architectures, and agent and Belief, Desires and Intentions (BDI) architectures. A list of projects with high payoff for modeling human performance in synthetic environments is provided as a conclusion.