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Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft
[article]
2021
arXiv
pre-print
An important challenge in reinforcement learning is training agents that can solve a wide variety of tasks. If tasks depend on each other (e.g. needing to learn to walk before learning to run), curriculum learning can speed up learning by focusing on the next best task to learn. We explore curriculum learning in a complex, visual domain with many hard exploration challenges: Minecraft. We find that learning progress (defined as a change in success probability of a task) is a reliable measure of
arXiv:2106.14876v1
fatcat:wpxs2t5otjeltgfqw4tp3mf5cu