Artificial Intelligence Testbed
A core goal of science is to produce predictive quantitative models. Recent work in artificial intelligence provides the opportunity to begin building predictive “pixels-to-actions” models of newborn organisms. Specifically, researchers have started building autonomous artificial agents that can learn to interact successfully with their environment, receiving only rewards and pixels as input (akin to the rewards and retinal images received by newborn animals). Importantly, these agents are formalized learning mechanisms in action. Thus, each agent can be thought of as a quantitative model for predicting what a newborn will learn given a specific set of experiences. If an artificial agent learns like a newborn animal, then the agent and animal should develop the same abilities when reared in the same environment.