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
Contact Networks, Immunity, and Evolution in Competing Cancer Epidemics. The project aims to evaluate evolutionary interactions between two transmissible cancer epidemics affecting Tasmanian devils and quantify their feedback on infection risk and epidemic behaviour. Using contact tracing and a phylogenetic framework we aim to quantify how tumour lineages evolve with each generation of infection and their effects on susceptibility to infection and disease progression. We expect to reveal the hos ....Contact Networks, Immunity, and Evolution in Competing Cancer Epidemics. The project aims to evaluate evolutionary interactions between two transmissible cancer epidemics affecting Tasmanian devils and quantify their feedback on infection risk and epidemic behaviour. Using contact tracing and a phylogenetic framework we aim to quantify how tumour lineages evolve with each generation of infection and their effects on susceptibility to infection and disease progression. We expect to reveal the host immuno-genetic basis underpinning cancer suppression and the adaptive capacity of populations in response to infectious diseases. This should significantly improve our ability to understand and manage this and other epidemic outbreaks in wildlife, as well as advancing our knowledge in cancer ecology and evolution.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