PyDreamer: model-based RL written in PyTorch + integrations with DM Lab and MineRL environments

This page summarizes the projects mentioned and recommended in the original post on /r/reinforcementlearning

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  • pydreamer

    PyTorch implementation of DreamerV2 model-based RL algorithm

  • dreamerv2

    Mastering Atari with Discrete World Models

    This is my implementation of Hafner et al. DreamerV2 algorithm. I found the PlaNet/Dreamer/DreamerV2 paper series to be some of the coolest RL research in recent years, showing convincingly that MBRL (model-based RL) does work and is competitive with model-free algorithms. And we all know that AGI will be model-based, right? :)

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  • planet

    Learning Latent Dynamics for Planning from Pixels (by google-research)

    Code for https://arxiv.org/abs/1811.04551 found: https://github.com/google-research/planet

  • dreamer

    Dream to Control: Learning Behaviors by Latent Imagination

    Code for https://arxiv.org/abs/1912.01603 found: https://github.com/danijar/dreamer

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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