We're aiming to develop a car game, which can be played against AI opponents, controlled by a neural network.

The project can be built with tup. http://gittup.org/tup/

The program depends on the following libraries:

• SFML (http://www.sfml-dev.org/)
• Boost (http://www.boost.org/)
• liblua (http://www.lua.org/)

To build, first create a variant: tup variant build/<name>.config. Then simply type tup.

Variants control the compiler and the flags. Supported compilers: gcc, clang.

If additional dependencies are needed, set the environment variables EXTRA_CPP_FLAGS (for compilation flags) and EXTRA_LD_FLAGS (for linker flags).

After building:

./build-<profile>/bin/car-game starts GUI with no neural network.

• Press T to turn telemetry graphs on/off.
• Press X to turn telemetry text on/off.
• Press A to turn AI on/off, you can drive the car yourself.
• Press C to show/hide the car.
• Press Y to show/hide rays.
• Press P to show/hide checkpoints.
• Press R to show/hide track boundary.
• Press N to show/hide track center line.
• Press G to show/hide track area.
• Press E to show/hide the trace of the current car.
• Press PgUp/PgDown to select different cars.

./build-<profile>/bin/car-game --game-type=learn starts crunching a population of neural networks. The best one is stored in best.car. This file is saved after each generation, so it can be viewed even while learning is in progress.

./build-<profile>/bin/car-game --neural-network best.car starts the same GUI, but this time with the neural network stored in best.car.

for full help on command line and config file parameters, run ./build-<profile>/bin/car-game --help.

The car physics are based on this tutorial: http://www.asawicki.info/Mirror/Car%20Physics%20for%20Games/Car%20Physics%20for%20Games.html

The neural network implementation is based on: http://www.ai-junkie.com/ann/evolved/nnt1.html