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This free, open source project hosted by GitHub aims to provide an easy way to train an AI agent.

The project consists of three components: the client, the server and the index. The role of the index is to provide a list of servers at a known address, so it's a simple program that servers contact when they become alive and when they are terminating to request the index to add/remove themselves, and the client contacts the index to get a list of available servers that the user may use to choose a server to connect to.

Both the client and the server are programs used as a publishing method for plug-ins. The server runs a virtual world and it may or may not be connected with a rendering device. Its main purpose is to keep and update a "scene graph" and to send streams of information to clients. Plug-ins are registered with the server to provide avatar types that handle both the way the avatar is being rendered (textures, meshes, etc) and the way it behaves (capabilities).

After choosing a server (that is, a virtual world), a client queries the server about the types of avatars it has and allows the user to choose an avatar. This avatar then needs to be associated with an actor - the brain of the avatar provided as a plug-in for the client. The actor may the start to learn to use the avatar or it may load previously stored knowledge and go interact with other actors incarnated in avatars.

The way this system is envisioned is as follows: the user runs both a server and a client on a local machine and lets the actor learn to deal with the avatar body (maybe in a simplified world) and, once that is done, the actor is connected with an avatar in a remote virtual world, where it may continue the training in the complex environment that results from other actors interacting with the virtual world.

The client side software that controls the avatar is called an actor and not a brain because it may contain additional components like DNA for evolutionary learning.

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