Designing Curriculum for Deep Reinforcement Learning in StarCraft II
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Hao, Daniel; Sweetser Kyburz, Penny; Aitchison, Matthew
Description
Reinforcement learning (RL) has proven successful in games, but suffers from long training times when compared to other forms of machine learning. Curriculum learning, an optimisation technique that improves a model’s ability to learn by presenting training samples in a meaningful order, known as curricula, could offer a solution. Curricula are usually designed manually, due to limitations involved with automating curricula generation. However, as there is a lack of research into effective...[Show more]
Collections | ANU Research Publications |
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Date published: | 2020-11 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/213263 |
Book Title: | AI 2020: Advances in Artificial Intelligence 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29–30, 2020, Proceedings |
DOI: | 10.1007/978-3-030-64984-5 |
Access Rights: | Open Access |
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File | Description | Size | Format | Image |
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SC2_Curriculum_Learning.pdf | paper | 232.3 kB | Adobe PDF | ![]() |
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