Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
IEEE

Federated Learning-Based Distributed Data Completion in Sparse Mobile CrowdSensing

Abstract: Sparse Mobile CrowdSensing (SMCS) is an emerging distributed data collection framework. As one of the core methods,data completion uses the collected data to fill in the missing data.
IEEE

Optimizing Plastic Waste Collection in Water Bodies Using Heterogeneous Autonomous Surface Vehicles With Deep Reinforcement Learning

Abstract: This letter presents a model-free deep reinforcement learning framework for informative path planning with heterogeneous fleets of autonomous surface vehicles to locate and collect plastic ...
Purdue University

A New Role, A Familiar Mission

Maria Wiltse has built her career around a central question: What difference did this make? As Lead Impact Evaluator for the Purdue University Office of Engagement (OoE), she is now focused on ...