有限复杂动态任务环境中交互的本质

Wayne D. Gray, John K. Lindstedt, C. Sibert, Matthew-Donald D. Sangster, Roussel Rahman, Ropafadzo Denga, Marc Destefano
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引用次数: 0

摘要

研究交互的本质需要任务环境,其中的变化可能由于环境的性质或该环境中主体的行为而产生。在动态环境中,agent选择什么都不做并不会阻止任务环境的变化。同样,在这样的环境中做出决策并不意味着基于当前信息的最佳决策将在任务环境变化时保持“最佳”。本章总结了正在进行的工作,这些工作带来了实验心理学、机器学习和高级统计分析的工具,以理解动态环境中涉及单个或多个交互代理的复杂任务中交互性能的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Essence of Interaction in Boundedly Complex, Dynamic Task Environments
Studying the essence of interaction requires task environments in which changes may arise due to the nature of the environment or the actions of agents in that environment. In dynamic environments, the agent’s choice to do nothing does not stop the task environment from changing. Likewise, making a decision in such environments does not mean that the best decision, based on current information, will remain “best” as the task environment changes. This chapter summarizes work in progress which brings the tools of experimental psychology, machine learning, and advanced statistical analyses to bear on understanding the complexity of interactive performance in complex tasks involving single or multiple interactive agents in dynamic environments.
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