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Commits on Jan 25, 2021

• Internal change

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Commits on Jan 18, 2021

• Add networks and configs for DQN LunarLander and MountainCar.

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• Remove support from static_argnums, as it is not a hashable type (and now causes an error). More details: https://github.com/google/jax/pull/4717

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Commits on Nov 24, 2020

• Add parameter for creating centered RMSProp optimizer.

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• Add support for min distributional value (`vmin`) in Rainbow rather than hardcoding it to be `-vmax`.

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• Add option to remove reward clipping.

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• Internal.

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• Flushing the summary results to ensure all summaries are logged.

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• Handle gym environment without the TimeLimit wrapper

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Commits on Oct 16, 2020

• Add notice of new learning curves and increase version number.

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• Add the Quantile (JAX) learning curves to the JSON plots.

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Commits on Oct 1, 2020

• Add reference to `identity_epsilon` in JAX DQN agent.

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• Make JAX linearly_decaying_epsilon function gin configurable.

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• Add LunarLander gin constants to the gym_lib

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• Use the doc_generator from https://github.com/tensorflow/docs

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Commits on Sep 2, 2020

• Add RMSProp as a possible optimizer for Jax agents.

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Commits on Aug 5, 2020

• Fix typo in requirements.txt

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• Add comments clarifying the optimizer for the JAX version of DQN.

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Commits on Aug 3, 2020

• Add a colab for visualizing trained Jax agents.

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• Add more details for JAX agents.

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• Add `elif` in example_viz_lib to distinguish IQN agents.

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• Announce Jax version of Dopamine on main page, add a README for Jax agents with downloadable links to trained agent checkpoints, and modify the agent visualizer library to also support IQN agents.

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• Increase PyPi version.

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• Fix reloading of network parameters for Jax agents.

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Commits on Jul 30, 2020

• Add __init__.py to new quantile directory.

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• Increase to version 3.1.3.

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• Add Jax version of QR-DQN.

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Commits on Jul 29, 2020

• Add resetting of graph and defaulting to load legacy checkpoints in agent visualizer colab.

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Commits on Jul 28, 2020

• Bump dopamine-rl version to 3.1.2.

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• Refresh and update Colab notebooks.

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• Set use_legacy_checkpoint to False by default for example_viz_lib.run().

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• Disable TF2 behaviors in run_experiment.Runner.

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• Lower minimum requirements for installing dopamine-rl package.

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• Update Dopamine install instructions.

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• Update Dopamine development environment dependencies.

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