Tyler Streeter
brain-inspired artificial general intelligence project banner

brain-inspired artificial general intelligence


Officially began in January 2006 (after I finished my MS thesis), but the core ideas date back to Fall 2004


This project represents my primary research goal: to design and build advanced intelligent machines (artificial general intelligence, or AGI) with mental capabilities similar to the mammalian brain. I believe this goal is becoming increasingly attainable because:

My general strategy for accomplishing this goal includes:

This project was originally inspired by my motor control evolution project, an example of a simulated entity learning complex motor control with very little instruction from the human programmer. That led me to study other forms of machine learning, especially those that require little help from a human teacher, i.e. reinforcement learning. My MS thesis work (i.e. Verve) was basically an initial AGI prototype implementation which was limited to just a few sensors and effectors.

Reinforcement learning is a great framework for designing intelligent machines which must learn from trial and error. However, it is only as effective as the machine's representation of the world. Thus, most of my research effort since 2006 has been focused on engineering an effective context representation, the internal representation of the outside world. In the brain this corresponds to the cerebral cortex.

The posters below describe the individual components of my system in a little more detail.


Poster for the 2008 Iowa State Emerging Technologies Conference Poster for the 2009 Artificial General Intelligence Conference