1. James Ihrig Awrad Mohammed Ali

2.  In our project we will use HyperNeat C++ to train a neural network to drive a car using TORCS as a platform.  This will be done by sending the Neural Networks generated from HyperNeat and receiving performance data from TORCS.

3.  We chose to do this project because we are interested in modeling agents in a continuous 3D environment.  We chose TORCS that because it is a an open source platform that has been used similarly in the past.

4. Connecting TORCS with NEAT is a very popular area it have been done before as we will see here:  In 2009 Luigi Cardamone, Daniele Loiacono and Pier Luca Lanzi did a very similar to what we are trying to do in our project.  Jorge Munoz, German Gutierrez and Araceli Sanchis create a controller for the game TORCS by learning how another controller or humans play the game and they use NEAT as one of the controllers.

5.  Communication from HyperNEAT ◦ Node Names ◦ Node Links ◦ Link Weights ◦ Unique ID for the network  Communication from TORCS ◦ Lap Times ◦ Accumulated error over lap ◦ Number of checkpoints reached ◦ Unique ID for the network

6.  Inputs ◦ Offset from center line ◦ Speed of vehicle ◦ Bias  Outputs ◦ Steering ◦ Gas Percentage ◦ Brake Percentage

7.  To calculate fitness we will make use of the number of segments passed, total laptime and the accumulated deviation from the centerline of the track.

8.  HyperNEAT  Range Sensors  Pie Slice Sensors

9. We will create sensors to detect how far the car from the edges.