Visually robust adversarial imitation learning from videos with contrastive learning
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 …
from videos in the presence of visual mismatch between agent and expert domains. We …
Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
Adversarial Imitation Learning (AIL) faces challenges with sample inefficiency because of its
reliance on sufficient on-policy data to evaluate the performance of the current policy during …
reliance on sufficient on-policy data to evaluate the performance of the current policy during …
A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations
This paper investigates how to incorporate expert observations (without explicit information
on expert actions) into a deep reinforcement learning setting to improve sample efficiency …
on expert actions) into a deep reinforcement learning setting to improve sample efficiency …
Sample-efficient Unsupervised Policy Cloning from Ensemble Self-supervised Labeled Videos
X Liu, Y Chen - arXiv preprint arXiv:2412.10778, 2024 - arxiv.org
Current advanced policy learning methodologies have demonstrated the ability to develop
expert-level strategies when provided enough information. However, their requirements …
expert-level strategies when provided enough information. However, their requirements …
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 …
of online Deep Reinforcement Learning (DRL) algorithms in large state and action space …