Search Results for author:
Found 3 papers, 1 papers with code
Deep active learning for nonlinear system identification
This simulated dataset can be used in a static deep active learning acquisition scheme referred to as global explorations.
Learning-based MPC from Big Data Using Reinforcement Learning
The state-of-the-art learning methods use RL to improve the performance of parameterized MPC schemes.
Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments
Attitude control of fixed-wing unmanned aerial vehicles (UAVs) is a difficult control problem in part due to uncertain nonlinear dynamics, actuator constraints, and coupled longitudinal and lateral motions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
