Left/Right brain in an RL agent

The brains of all bilaterally symmetric animals on Earth are divided into left and right hemispheres. The anatomy and functionality of the hemispheres have a large degree of overlap, but they specialize to possess different attributes. This principle is poorly understood and has not been exploited in AI/ML. The right hemisphere is more dominant for novelty, and the left for routine. Activity slowly moves to the left hemisphere as a task is perfected. In this project, we apply that principle to continual RL, where new tasks are introduced over time. We will create a ‘generalist’ right network that can perform novel tasks while a left network has time to become proficient, providing a more maintained level of competence across new tasks - a critical characteristic for practical agents to operate in realistic environments.