AI researchers share data on how we sort options, make decisions
Researchers have been able to prove that the brain learns from experience since Russian physiologist Ivan Pavlov conditioned dogs to drool in anticipation of food. In the 100-plus years since, however, scientists studying the brain and the emerging field of artificial intelligence (AI) have been homing in how that happens. A new paper in Nature, “A distributional code for value in dopamine-based reinforcement learning,” goes further in exploring how experience and options are sorted in making decisions. At issue, explained neurobiologist Naoshige Uchida, professor of cellular and molecular biology and one of the paper’s authors, is “reward prediction” — essentially how well a brain can foresee the risks and rewards of any particular action. Uchida’s lab studies the production of the neurotransmitter dopamine in mice, tracing the chemical decision-making process: Will going after that cheese result in getting stuck in a trap? Is it worth running that maze? The field of AI...