Discovery Projects - Grant ID: DP240103278

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP240103278

Funding Status
Active

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Funded Activity Summary

Learning to Reason in Reinforcement Learning. Deep Reinforcement Learning (RL) uses deep neural networks to represent and learn optimal decision-making policies for intelligent agents in complex environments. However, most RL approaches require millions of episodes to converge to good policies, making it difficult for RL to be applied in real-world scenarios taking significant resources. This project aims to equip RL with capabilities such as counterfactual reasoning and outcome anticipation to significantly reduce the number of interactions required, improve generalisation, and provide the agent with the capability to consider the cause-effects. These improvements would narrow the gap between AI and human capabilities and broaden the adoption of RL in real-world applications.

Funded Activity Details

Start Date: 2024

End Date: 12-2026

Funding Scheme: Discovery Projects

Funding Amount: $544,551.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Knowledge representation and reasoning | Computer vision | Machine learning | Reinforcement learning |

ANZSRC Socio-Economic Objective (SEO)

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