
Jeff Clune
TalkRL: The Reinforcement Learning Podcast
Open-Ended Algorithms in Machine Learning
Many RL algorithms could take advantage of lots of computing a simulator and then learn a lot of stuff. It would be really cool to try to use the principles of Go Explorer in a problem that doesn't have simulators. So sounds like hard exploration problems that have really good simulators would be suitable for Go Explorer. And boom, you might zero-shot transfer to the real world.
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