Autonomous Intelligent Reinforcement

Interpreted Symbolism

AIRIS is a causality based artificial intelligence that teaches itself how to operate in any given environment

Project Features

Small Data
Explainable
Transparent
Goal Agnostic
Continuous Learning

FAQ

Is there a paper?

I would love to have a paper about this, but I’m a self-taught hobbyist game developer not an academic. I’ve never written a paper and wouldn’t know how. If you have experience in writing ML papers and can help, please let me know!

Where’s the code?

You can find the source code for the build from “AIRIS Project 2023 Demonstration” here!

About AIRIS

AIRIS is an Artificial Intelligence project based on a new Machine Learning technique called “Reinforcement Inferred Causality”.

Anatomy of Prediction and Predictive AI

In the previous article, Friendly AI via Agency Sustainment, we talked about a potential solution to the Control Problem of Artificial General Intelligence. One of the requirements of that proposition is an AI that is capable of predicting the behavior of other agents. In this article, we will discuss how humans make such predictions and…

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