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jax-dreamer

An implementation of Dreamer, a model-based reinforcement learning algorithm which uses model-generated (a.k.a 'imagined') experience to learn a policy in a generalized policy iteration scheme.

Installation

conda create -n jax-dreamer python=3.7
conda activate jax-dreamer
pip3 install -r requirements.txt

Experiments

python3 train.py --configs defaults pendulum --log_dir pendulum