This project shows that MLP (Multi layer perceptrons) can be used in videogames to create characters with advanced AI capabilities.The main advantage of this aproach is the ability that neural networks have to simulate the natural learning process.
In this example, Mario is controlled by the human player for a while, as Mario plays, information about his decisions is stored, and then the neural network is trained against this data. When the training is done, Mario leaves the scene and Luigi starts to play commanded by the neural network. Alternatively Mario can be controlled by a classical AI (if-else logic) so the user doesn't have to play the game and the neural network learns from this classical AI.
This architecture makes possible creating games where AI characters learn from the human user, evolving the game as the human player acquires new skills.
NetBeans project is provided in addition to the executable JAR. The following libraries are used:
- Encog http://www.heatonresearch.com/encog
- Slick2D & LWJGL http://slick.ninjacave.com/ (http://slick.ninjacave.com/wiki/index.php?title=Setting_up_Slick2D_with_NetBeansIDE)
Further explanations can be found here (in spanish): https://www.youtube.com/watch?v=yN3bPRHLd5s