@@ -43,11 +43,7 @@ importing the ML-Agents assets into it:
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Your Unity ** Project** window should contain the following assets:
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- <p align =" left " >
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- <img src="images/roller-ball-projects.png"
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- alt="Project window"
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- width="250" border="10" />
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- </p >
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+ ![ Unity Project Window] ( images/roller-ball-projects.png ) {: style="width:250px"}
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## Create the Environment
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@@ -64,11 +60,7 @@ to seek, and a Sphere to represent the Agent itself.
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1 . Set Transform to Position = ` (0, 0, 0) ` , Rotation = ` (0, 0, 0) ` , Scale =
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` (1, 1, 1) ` .
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- <p align =" left " >
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- <img src="images/roller-ball-floor.png"
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- alt="The Floor in the Inspector window"
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- width="400" border="10" />
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- </p >
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+ ![ Floor Inspector window] ( images/roller-ball-floor.png ) {: style="width:400px"}
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### Add the Target Cube
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@@ -78,11 +70,7 @@ to seek, and a Sphere to represent the Agent itself.
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1 . Set Transform to Position = ` (3, 0.5, 3) ` , Rotation = ` (0, 0, 0) ` , Scale =
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` (1, 1, 1) ` .
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- <p align =" left " >
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- <img src="images/roller-ball-target.png"
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- alt="The Target Cube in the Inspector window"
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- width="400" border="10" />
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- </p >
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+ ![ Target Cube Inspector window] ( images/roller-ball-target.png ) {: style="width:400px"}
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### Add the Agent Sphere
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@@ -108,11 +96,7 @@ To do so:
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1 . Drag the Floor, Target, and RollerAgent GameObjects in the Hierarchy into the
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TrainingArea GameObject.
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- <p align =" left " >
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- <img src="images/roller-ball-hierarchy.png"
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- alt="The Hierarchy window"
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- width="250" border="10" />
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- </p >
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+ ![ Hierarchy window] ( images/roller-ball-hierarchy.png ) {: style="width:250px"}
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## Implement an Agent
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@@ -360,11 +344,8 @@ with our Agent script.
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- ` Actions ` > ` Continuous Actions ` = 2
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In the inspector, the ` RollerAgent ` should look like this now:
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- <p align =" left " >
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- <img src="images/roller-ball-agent.png"
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- alt="The Agent GameObject in the Inspector window"
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- width="400" border="5" />
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- </p >
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+
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+ ![ Agent GameObject Inspector window] ( images/roller-ball-agent.png ) {: style="width:400px"}
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Now you are ready to test the environment before training.
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