Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time ....Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.Read moreRead less
Remote presence for guidance on physical tasks. This project aims to transform remote collaboration on physical tasks. Current systems for remote collaboration on physical tasks are not as effective as working face-to-face. This could be overcome by sharing non-verbal cues, designing systems to account for cultural issues, and using a new model of communication. This project will develop theories and interaction methods for remote guidance based on natural non-verbal communication cues and cultu ....Remote presence for guidance on physical tasks. This project aims to transform remote collaboration on physical tasks. Current systems for remote collaboration on physical tasks are not as effective as working face-to-face. This could be overcome by sharing non-verbal cues, designing systems to account for cultural issues, and using a new model of communication. This project will develop theories and interaction methods for remote guidance based on natural non-verbal communication cues and cultural issues. This project is expected to benefit industries with widely distributed multi-cultural workforces such as mining, defence and medicine.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
Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuo ....Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuous real-time observations and will allow users to remotely monitor water quality; alerting them to pollutant levels, enabling immediate action to be taken to prevent environmental damage. The system is low-cost, facilitating mass adoption, yet delivers an analytical performance comparable to leading laboratory analysers. Read moreRead less
Global Citizen Deliberation: Analysing a Deliberative Documentary. The project will enact and film the world’s first truly global citizens’ deliberation, a global citizens’ assembly (GCA) on genome editing, and proceed to analyse the impact of the ‘deliberative documentary’ film on public understanding of complex, fast-evolving science and technology. It will investigate the cross-cultural capacity of citizens to deliberate complex value-laden issues, and so ascertain prospects for an informed g ....Global Citizen Deliberation: Analysing a Deliberative Documentary. The project will enact and film the world’s first truly global citizens’ deliberation, a global citizens’ assembly (GCA) on genome editing, and proceed to analyse the impact of the ‘deliberative documentary’ film on public understanding of complex, fast-evolving science and technology. It will investigate the cross-cultural capacity of citizens to deliberate complex value-laden issues, and so ascertain prospects for an informed global public response to challenges posed by genome editing. Research will test the effects of the deliberative documentary on viewers, examining benefits of communicating complex issues via the work of the GCA. Other benefits include improving public trust in governance and advancing the Australian film industry.
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