Nathan Lambert
@natolambert·8K subscribers·36 videos
[Paper Summary] The Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Posted
March 24, 2021
Views
237
Likes
4
Engagement
1.69%
March 24, 2021
237
4
1.69%
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3:00Now PlayingThis is one of those papers that changes your views on things. I knew hyper-parameters were important to deep RL and I knew that model-based RL is a more complicated system to build and deploy, but magnitude of the effects of tuning parameters in MBRL is boggling. In breaking the simulator with a really simple MBRL algorithm, you can learn a lot more about the state of the field.
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