Pre-training with RL: APT

Behave From the Void: Unsupervised Active Pre-training paper The paper, Behave From the Void: Unsupervised Active Pre-training, proposed a new method for pretraining RL agents, APT , which is claimed to beat all baselines on DMControl Suite. As the abstract pointed out: the key novel idea is to explore the environment by maximizing a non-parametric entropy computed in a abstract representation space. This blog will take a look at the motivation, method and explanation of the paper, as well as compare it with the other AAAI paper....

September 24, 2022 · Dibbla

Pre-training with RL: APT

Behave From the Void: Unsupervised Active Pre-training paper The paper, Behave From the Void: Unsupervised Active Pre-training, proposed a new method for pretraining RL agents, APT , which is claimed to beat all baselines on DMControl Suite. As the abstract pointed out: the key novel idea is to explore the environment by maximizing a non-parametric entropy computed in a abstract representation space. This blog will take a look at the motivation, method and explanation of the paper, as well as compare it with the other AAAI paper....

September 24, 2022 · Dibbla