Robot AI Movement 🤖

This project simulates a simple robot that decides how to move based on sensor input using a basic artificial intelligence model.

How It Works

1. Initialization:

   • The robot starts with a random set of weights. These weights help the robot decide its actions based on sensor data.

2. Sensor Input:

   • The robot receives input from its environment, such as the distance to an obstacle. In this example, we use a fixed value of 0.3.

3. Forward Propagation:

   • The sensor input and a bias value (always 1.0) are combined into a matrix. The robot uses the random weights to perform a calculation called "forward propagation" to determine a score.

4. Decision Making:

   • The score is passed through a function called sigmoid, which transforms it into a value between 0 and 1.
   • If this value is greater than 0.5, the robot decides to move forward. Otherwise, it decides to turn left.

5. Robot Movement:

   • Based on the decision, the robot either moves forward a set distance or turns left by a specified angle.

6. Output:

   • Finally, the program prints the robot's action and its new position after moving.

Example

When you run the program:

• It initializes the weights.
• The robot checks its sensor input.
• It decides whether to move forward or turn left.
• It updates its position accordingly.