Website
http://dataportal.arc.gov.au/NCGP/API/grants/DE220100265
Funding Status
Active
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Funded Activity 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 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.Funded Activity Details
Start Date: 10-2022
End Date: 10-2025
Funding Scheme: Discovery Early Career Researcher Award
Funding Amount: $417,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Neural, Evolutionary and Fuzzy Computation | Artificial Intelligence and Image Processing | Computer-Human Interaction
ANZSRC Socio-Economic Objective (SEO)
Information Processing Services (incl. Data Entry and Capture) |
