Using virtual reality, modelling, control, machine & deep learning to investigate behavioural dynamics of human machine interaction from a multiagent

起点将是利用数学建模、机器和深度学习，确定执行合作知觉运动任务的人类群体的认知和行为过程。该项目还将寻求揭示机制在多大程度上导致在复杂的多智能体环境任务中出现强有力的多智能体人类协调。其目的将是设计能够与人类合作执行联合羊群和人群控制任务的人工代理，并利用实验观察来设计能够驱动此类代理的反馈控制算法和认知架构

Starting point will be to identify cognitive and behavioural processes of groups of humans performing cooperative perceptual motor tasks, with the use of mathematical modelling, machine and deep learning. The project will also seek to unfold the degree to which mechanism lead to the emergence of robust multi-agent human coordination in complex multi-agent-environment tasks in general. The aim will be to design artificial agents able to perform joint herding and crowd control tasks in cooperation with humans and use observations from experiments to design feedback control algorithms and cognitive architectures able to drive such agents