Last Updated: 4/11/2019
Status: In Progress
Objective
Develop an Artificial General Intelligence (AGI) agent which can learn to function in a continuous real-time environment through various means of training using a general architecture which is not specific to any task, ability, or robot design. The goal is not human-level intelligence, rather the highest functioning general intelligence achievable on modest hardware.
Goals
The agent should be able to make sense of itself and its environment quickly – similar to a human or animal.
The agent should be able to develop a broad understanding of the world through experiences and interactions in the environment.
The agent should be able to learn how to accomplish tasks which are fundamentally different from each other, and retain the skills learned.
The agent should be able to use relevant knowledge learned from prior experiences in order to solve new problems.
The agent should be able to learn how to communicate with a human (using virtual reality) or another agent in the environment.
General Description
The agent is general, and is designed to be able to learn to function in any arbitrary and unknown environment. In other words, the agent code is independent of the environment. It doesn’t have any prior knowledge of the world or itself at startup.
The agent learns from experiencing the world as it finds ways to meet objectives. It determines the best actions to take based on what has been learned. It must learn everything it needs to know to operate.
Since the world is open and continuous, the agent is free to take any one of an infinite number of paths to anywhere. Therefore, curriculum training using objectives is used to guide the agent to learning opportunities where it can discover and learn new things.
The environment runs in real-time and is indifferent to any agents who come in to play. Since the agent runs asynchronously, it has to be able to think fast enough to keep up with the environment.