**重要：教師閱讀** 載入（或創建）您課程/活動的參數
** 此部分供教師閱讀，提供更多有關有效使用AlphAI的知識 **
連接到機器人後，將顯示以下畫面。
請注意，這只是默認AI專案的畫面，並不是您課程/活動的AI專案。
** This part is for TEACHER READING. It gives more knowledge about using AlphAI effectively. **
After connecting to the robot, the following screen will be shown.
Note that it is just the screen for the default AI project. It is NOT the AI project for your lesson/activity.
載入參數 <Load Parameter>
要啟動您特定的AI專案（例如機器人競速、線路追蹤或人臉識別），您必須正確設置相應的參數。這些參數包括:-
- 輸入 - 您將使用哪些感測器？（如下所示）
- 輸出 - 您將使用哪些動作/標記輸出？（如下所示）
- AI - 您將使用哪種AI學習方法/哪種算法？（如下所示）
- 可視化 - 您希望如何顯示神經網絡？
To start your specific AI project (e.g. Robot Race, Line Tracking, or Facial Recognition), you must set up the parameters properly for it. Parameters are:-
- Input - what sensor(s) are you going to use? (shown below)
- Output - what action(s)/labeled-output(s) are you going to use? (shown below)
- AI - what algorithm (AI learning method) are you going to use? (shown below)
- Visualization - how do you want to display the Neural Network?
有三種方法可以載入/創建AI參數 <There are 3 Methods to Load/Create AI Parameters.>
方法1 - 載入示範參數
- AlphAI附帶一組示範課程。每個示範課程都有一組現成的參數，您可以輕鬆地載入這些參數。
方法2 - 載入已保存的參數
- 您還可以載入由他人為您創建的參數文件，或者您自己在課程之前為自己或學生創建的參數文件。
方法3 - 創建（或編輯）自己的AI參數
- 如果您想嘗試自己的AI實驗，您可以創建（或修改）並保存自己的AI參數。
Method 1 - Load the Demo Parameters
- AlphAI comes with a set of Demo lessons. Each of these Demo Lessons has a ready-made parameters which you can load easily.
Method 2 - Load the Saved Parameters
- You can also load the parameter file which someone has created for you or you have create for yourself or for your students before teh lesson.
Method 3 - Create (or Edit) your Own AI Parameters
- If you want to try your own AI experiment, you can create (or modify) and save your own AI parameters.
方法1 - 載入示範參數 <Method 1 - Load the Demo Parameters>
方法2 - 載入已保存的參數 <Method 2 - Load the Saved Parameters>
方法3 - 創建（或編輯）自己的AI參數 <Method 3 - Create (or Edit) your Own AI Parameters>
使用「感測器」、「動作」、「人工智能」等等, 來創建您自己的AI專案的參數。
範例1 - 我們的機器人車避免撞牆
• 輸入（感測器）- 8 x 6攝像頭（灰度）
• 輸出（動作）- 前進，原地轉彎（左轉和右轉）
• 人工智能- 學習類型=監督式學習；算法=神經網絡
範例2 - 人臉識別
• 輸入（感測器）- 32 x 24攝像頭（3種顏色）
• 輸出（動作）- 使用學生姓名創建自定義標籤作為輸出
• 人工智能- 學習類型=監督式學習；算法=神經網絡
Use the "Sensors", "Actions", "A.I.", ... etc. to create your the parameters for your own A.I. projects.
Example 1 - our robot car avoids hitting the wall
- Input (Sensor) - 8 x 6 camera (grayscale)
- Output (Actions) - Forward, Turn in Place (left and right)
- A.I. - learning type = supervised learning; algorithm = neural network
Example 2 - facial recognition
- Input (Sensor) - 32 x 24 camera (3-colors)
- Output (Actions) - create customized labels with students' names as Outputs
- A.I. - learning type = supervised learning; algorithm = neural network
