Today’s RL algorithms are great at exploiting a particular environment, terrible at using that knowledge in new situations. Here’s a new environment which is already helping us understand why, and which may help develop RL algorithms that generalize:
We’re releasing CoinRun, an environment generator that provides a metric for an agent’s ability to generalize across new environments - blog.openai.com/quantifying-…
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This is our third major attempt in the past two years (Universe, Retro Contest) to develop a platform for RL generalization. Each time, we’ve made the task easier — but more focused on the core generalization challenge. Already seeing promising results on CoinRun.
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Looks interesting! Seems very related to our paper on Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation arxiv.org/pdf/1806.10729.pdf @togelius @nojustesen
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