About

The main motivation was to have a simple game framework allowing students to jump right away in AI without having to code their own game from scratch. With AI.Bootcamp, students are only required to know how to code in C++ using Visual Studio, learn how the AIBot Client works, and launch couple of scripts in console window to build, deploy and test their AIBot. When the engine is already installed and configured, it usually takes less than 5 minutes to code and test a simple random AIBot.

Another important consideration was to remove anything related to the execution layer (animation control, sounds, etc.). Not that these aspects aren't important to create good game AI, on the contrary, but it was adding a level of complexity on top of the what was the main focus of the course i.e. game AI algorithms, decision-making architectures and implementation technics (FSM/HSM, BT, etc.). Just by focusing on decision-making models, a lot of the inherent complexity of controlling NPCs in a scene was enough to provide challenging situations.

In the same line of thought, the decision to remove Fun Factor considerations was an important one too. As much as the game industry requires to know how to balance game AI behaviors to create fun situations, it takes some time to experiment with the basic game AI algorithms and technics to understand what their limitations and advantages are. This explains why the AI.Bootcamp challenge is focussed on creating an AIBot able to solve each level in a more or less optimal way, instead of the more realistic scenario where the Player is in the loop.