Archives for meta-reinforcement learning
Meta Reinforcement learning(Meta-RL) can be explained as performing meta-learning in the field of reinforcement learning. where including meta-learning models in reinforcement learning we can grow the model to perform a variety of tasks.
This post is in continuation with our previous article about Alchemy, the very first benchmark on meta-Reinforcement Learning. Deepmind with the University of London has released an open-source benchmark environment for meta-RL : Alchemy: A structured task distribution for meta-reinforcement learning by Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck,…
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