Adversarial imitation learning from visual observations using latent information

V Giammarino, J Queeney, IC Paschalidis - arxiv preprint arxiv …, 2023 - arxiv.org
We focus on the problem of imitation learning from visual observations, where the learning
agent has access to videos of experts as its sole learning source. The challenges of this …

A bilateral teleoperation system with learning-based cognitive guiding force

Z Ma, D Shi, Z Liu, J Yu, P Huang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article investigates the problem involving a fuzzy logic system (FLM)-based bilateral
teleoperation system with a unified impedance/admittance structure and learning-based …

Visually robust adversarial imitation learning from videos with contrastive learning

V Giammarino, J Queeney, IC Paschalidis - arxiv preprint arxiv …, 2024 - arxiv.org
We propose C-LAIfO, a computationally efficient algorithm designed for imitation learning
from videos in the presence of visual mismatch between agent and expert domains. We …

Generative Upper-Level Policy Imitation Learning With Pareto-Improvement for Energy-Efficient Advanced Machining Systems

Q **ao, B Niu, Y Tan, Z Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The potential intelligence behind advanced machining systems (AMSs) offers positive
contributions toward process improvement. Imitation learning (IL) offers an appealing …

A Novel Lane-Change Decision-Making With Long-Time Trajectory Prediction for Autonomous Vehicle

X Wang, J Hu, C Wei, L Li, Y Li, M Du - IEEE Access, 2023 - ieeexplore.ieee.org
In the process of autonomous vehicle lane changing, a reliable decision-making system is
crucial for driving safety and comfort. However, traditional decision-making systems have …

Off-policy imitation learning from visual inputs

Z Cheng, L Shen, D Tao - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
Recently, various successful applications utilizing expert states in imitation learning (IL)
have been witnessed. However, IL from visual inputs (ILfVI), which has a greater promise to …

Quantum Imitation Learning

Z Cheng, K Zhang, L Shen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Despite remarkable successes in solving various complex decision-making tasks, training
an imitation learning (IL) algorithm with deep neural networks (DNNs) suffers from the high …

On the use of expert data to imitate behavior and accelerate Reinforcement Learning

V Giammarino - 2024 - search.proquest.com
This dissertation examines the integration of expert datasets to enhance the data efficiency
of online Deep Reinforcement Learning (DRL) algorithms in large state and action space …