Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal
robots. Although techniques for automating the process exist, most involve local function …

This paper highlights the role that reinforcement learning can play in the optimization of
treatment policies for chronic illnesses. Before applying any off-the-shelf reinforcement learning …

Dynamic treatment regimes are of growing interest across the clinical sciences because
these regimes provide one way to operationalize and thus inform sequential personalized …

We present a general and detailed development of an algorithm for finite-horizon fitted-Q
iteration with an arbitrary number of reward signals and linear value function approximation …

We introduce new, efficient algorithms for value iteration with multiple reward functions and
continuous state. We also give an algorithm for finding the set of all nondominated actions in …

PURPOSE Rapid increases in technology and data motivate the application of artificial
intelligence (AI) to primary care, but no comprehensive review exists to guide these efforts. Our …

The selection of effective genes that accurately predict chemotherapy responses might improve
cancer outcomes. We compare optimized gene signatures for cisplatin, carboplatin, and …

Dynamic treatment regimes (DTRs) operationalize the clinical decision process as a sequence
of functions, one for each clinical decision, where each function maps up‐to‐date patient …

Frequently, acquiring training data has an associated cost. We consider the situation where
the learner may purchase data during training, subject TO a budget. IN particular, we …

Objective: Internationally, primary care practice had to transform in response to the COVID
pandemic. Informatics issues included access, privacy, and security, as well as patient …