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Add use curiosity in Hallway example environment #1952

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Merged
merged 2 commits into from
Apr 16, 2019

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sdiao
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@sdiao sdiao commented Apr 16, 2019

Hallway example takes a long time to train. To speed up training, we can enable curiosity. This change is to add a suggestion in the doc in case our customers want to speed up the Hallway example training.

@sdiao sdiao requested a review from harperj April 16, 2019 21:01
@sdiao sdiao changed the base branch from master to develop April 16, 2019 21:02
@@ -246,6 +246,7 @@ If you would like to contribute environments, please see our
`VisualHallway` scene.
* Reset Parameters: None.
* Benchmark Mean Reward: 0.7
* To speed up training, you can enable curiosity by adding `use_curiosity: true` in `config/trainer_config.yaml`
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Is the intention to have space prior to the asterisk?

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yes. It looks all examples have the same list of bullet points (Set-up, Goal,..., Benchmark Mean reward). I want to keep the overall structure, and only add enabling curiosity to achieve the benchmark mean reward faster. So I add this optimization under the benchmark mean reward. Let me know if there is a better place to add a note of enabling curiosity.

@mmattar mmattar merged commit 45c535b into develop Apr 16, 2019
mantasp added a commit that referenced this pull request Jun 14, 2019
* develop-barracuda-0.2.0: (80 commits)
  Restored compatibility fixes for some Androids
  Upgraded to Barracuda 0.2.1, fixes issues with discrete action models
  First stage of ML Agents update to Barracuda 0.2.x
  Update Learning-Environment-Create-New.md (#1993)
  Format gym_unity using black
  [Documentation] Added information for the environments the trainer cannot train with the default configurations (#1995)
  [Documentation] SetReward method (#1996)
  [Gym] Added no_graphics argument (#1997)
  Develop black format fix (#1998)
  Add exception for external brains and array-ify (#1971)
  Enable the switching of scene to control mode, load the corresponding scene using environment variable (#1956)
  Add use curiosity in Hallway example environment (#1952)
  Python code reformat  via [`black`](https://github.com/ambv/black). Features: - Reformat code via black. - Adding circleci configurations. - Add contribution guidelines.
  Fix custom protobuf link in README
  Bumping gym_unity version
  Release 0.8.1 to fix pypi issues
  Explicitly adding all packages as imports
  Migration doc fixes
  Basic Retrain (#1929)
  Updated the 3dballhard model
  ...

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@awjuliani awjuliani deleted the develop-sdiao-update-example-env branch July 23, 2019 20:18
LeSphax pushed a commit to LeSphax/ml-agents-1 that referenced this pull request May 3, 2020
@github-actions github-actions bot locked as resolved and limited conversation to collaborators May 18, 2021
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3 participants