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Update Learning-Environment-Examples.md (#1188)

/develop-generalizationTraining-TrainerController
Arthur Juliani 6 年前
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      docs/Learning-Environment-Examples.md

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docs/Learning-Environment-Examples.md


* Set-up: A platforming environment where the agent can push a block around.
* Goal: The agent must push the block to the goal.
* Agents: The environment contains one agent linked to a single Brain.
* Agent Reward Function:
* -0.0025 for every step.
* +1.0 if the block touches the goal.
* Brains: One Brain with the following observation/action space.
* Vector Observation space: (Continuous) 70 variables corresponding to 14
ray-casts each detecting one of three possible objects (wall, goal, or
block).
* Vector Action space: (Continuous) Size of 2, corresponding to movement in X
and Z directions.
* Visual Observations (Optional): One first-person camera. Use
`VisualPushBlock` scene.
* Agents: The environment contains one agent linked to a single brain.
* Agent Reward Function:
* -0.0025 for every step.
* +1.0 if the block touches the goal.
* Brains: One brain with the following observation/action space.
* Vector Observation space: (Continuous) 70 variables corresponding to 14
ray-casts each detecting one of three possible objects (wall, goal, or block).
* Vector Action space: (Discrete) Size of 6, corresponding to turn clockwise
and counterclockwise and move along four different face directions.
* Visual Observations (Optional): One first-person camera. Use `VisualPushBlock` scene.
* Reset Parameters: None.
* Benchmark Mean Reward: 4.5
* Optional Imitation Learning scene: `PushBlockIL`.

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