Christopher Symons, Ph.D. | Sep 3, 2021 | Artificial Intelligence, Behavioral Science, Blog
Lirio’s Behavioral Reinforcement Learning Lab (BReLL) recently published a paper describing a new approach, the Limited Data Estimator, for comparing reinforcement learning policies using limited historical data.
Christopher Symons, Ph.D. and Clayton Webster, Ph.D. | Jul 1, 2020 | Artificial Intelligence, Blog, Digital Health
Lirio’s AI Research team recently developed a novel adaptive stochastic gradient-free (ASGF) approach for solving some of the most difficult optimization challenges in machine learning. This innovative optimization algorithm, which is simple to implement and does not...