School for AI (or School for short) is a world within Brain Simulator, coupled with an intuitive graphical interface. The training provided by School is separated into learning tasks. A single learning task teaches or tests preferably a single new skill or ability. A collection of learning tasks forms a curriculum. An agent is expected to gradually acquire knowledge as it is progressing through the curriculum. It should acquire knowledge from one learning task and then leverage that knowledge to acquire knowledge from the next learning task faster and with greater ease. We call this accumulation of skills “gradual learning” and we talk about it in more detail in our Framework document.
The training can occur in a range of environments. We’ve prepared a basic 2D environment (RoguelikeWorld), an advanced 2D environment (ToyWorld), and a basic 3D environment (3D version of ToyWorld). A single curriculum can train the same architecture on multiple different environments.
School for AI does not explicitly separate the training and testing phases. It prefers life-long learning – the agent is learning continuously, without any interruption. The testing is performed during training. This of course poses certain requirements on the datasets – the environments that are used in school are generated rather than fixed. This allows a fast learning agent to progress through the curriculum in shorter time than a slow learning agent. We’re planning to include existing datasets (both fixed and interactive) in School to provide a single interface and make using different datasets a breeze.
The learning tasks that appear in the current version of School are based on our Agent Development Roadmap. They teach the agent basic skills like object detection, color classification, or path finding. We took care to ensure that it is easy to add new learning tasks to the environment. We’ll be happy if you go on, get Brain Simulator code from GitHub and create a learning task of your own!
The school communicates with the agent through a fixed interface. The interface allows the agent to move around the environment, move its focus around the scene and interact with the objects found within the environment (when applicable).
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