Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demand ....Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demands when dealing with multiple stimuli or performing multiple tasks concurrently under time pressure. The project aims to provide the basic research that is needed to extend psychological models of choice to complex ‘real-world’ tasks, such air traffic control and maritime surveillance.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100002
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes ....ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.Read moreRead less