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Designing Curriculum for Deep Reinforcement Learning in StarCraft II

Hao, Daniel; Sweetser Kyburz, Penny; Aitchison, Matthew


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]

CollectionsANU Research Publications
Date published: 2020-11
Type: Conference paper
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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