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6 changes: 1 addition & 5 deletions docs/Installation.md
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Expand Up @@ -58,11 +58,7 @@ If you'd like to use Docker for ML-Agents, please follow

## Unity Packages

You can download ML-Agents as Unity Packages:

* [ML-Agents with TensorflowSharp Plugin](https://s3.amazonaws.com/unity-ml-agents/0.3/ML-AgentsWithPlugin.unitypackage)
* [ML-Agents without TensorflowSharp Plugin](https://s3.amazonaws.com/unity-ml-agents/0.3/ML-AgentsNoPlugin.unitypackage)
* [TensorflowSharp Plugin Only](https://s3.amazonaws.com/unity-ml-agents/0.3/TFSharpPlugin.unitypackage)
You can download the TensorflowSharp Plugin as a Unity package [here](https://s3.amazonaws.com/unity-ml-agents/0.3/TFSharpPlugin.unitypackage).
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TensorflowSharp --> TensorFlowSharp

  • Capitalize F
  • Add link for the uninitiated

Plugin --> plugin


## Help

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6 changes: 1 addition & 5 deletions docs/localized/zh-CN/docs/Installation.md
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Expand Up @@ -56,11 +56,7 @@ Unity Assets。`python` 目录包含训练代码。

## Unity 包

您可以通过 Unity 包的形式下载 ML-Agents:

* 带 TensorflowSharp 插件的 ML-Agents([AWS S3链接](https://s3.amazonaws.com/unity-ml-agents/0.3/ML-AgentsWithPlugin.unitypackage),[百度盘链接](https://pan.baidu.com/s/1qkWOqb0meyTorBG-So_PfA))
* 不带 TensorflowSharp 插件的 ML-Agents([AWS S3链接](https://s3.amazonaws.com/unity-ml-agents/0.3/ML-AgentsNoPlugin.unitypackage),[百度盘链接](https://pan.baidu.com/s/1K8fZFslW6PWNgmWA6oO4Yg))
* 仅包含 TensorflowSharp 插件([AWS S3链接](https://s3.amazonaws.com/unity-ml-agents/0.3/TFSharpPlugin.unitypackage),[百度盘链接](https://pan.baidu.com/s/1s0mJN8lvuxTcYbs2kL2FqA))
您可以通过 Unity 包的形式下载TensorflowSharp 插件([AWS S3链接](https://s3.amazonaws.com/unity-ml-agents/0.3/TFSharpPlugin.unitypackage),[百度盘链接](https://pan.baidu.com/s/1s0mJN8lvuxTcYbs2kL2FqA))

## 帮助

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138 changes: 67 additions & 71 deletions unity-environment/Assets/ML-Agents/Examples/Basic/Scene.unity
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Expand Up @@ -190,7 +190,7 @@ public void DecideAction(Dictionary<Agent, AgentInfo> agentInfo)
foreach (Agent agent in agentList)
{
List<float> state_list = agentInfo[agent].stackedVectorObservation;
for (int j = 0; j < brain.brainParameters.vectorObservationSize * brain.brainParameters.numStackedVectorObservations; j++)
for (int j = 0; j < stateLength * brain.brainParameters.numStackedVectorObservations; j++)
{
inputState[i, j] = state_list[j];
}
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