Discovery Early Career Researcher Award - Grant ID: DE200100245

Funding Activity

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Funded Activity Summary

Bayesian nonparametric learning for practical sequential decision making. This project aims to develop new methods to support practical sequential decision making under uncertainty. It expects to pave the way for the next generation of sequential decision making uniquely characterised by uncertainty modelling, high sample-efficiency, efficient environment change adaptation, and automatical reward function learning. The expected outcomes will advance machine learning knowledge with a new deep learning schema for data modelling and sequential decision-making knowledge with a novel deep reinforcement learning methodology. These developments have immediate applications in autonomous vehicles, advanced manufacturing, and dynamic pricing, with scientific, economic, and social benefits for Australia and the world.

Funded Activity Details

Start Date: 01-05-2020

End Date: 30-04-2024

Funding Scheme: Discovery Early Career Researcher Award

Funding Amount: $410,518.00

Funder: Australian Research Council