6 papers
DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-domain Reinforcement Learning
Linh Le Pham Van, Minh Hoang Nguyen, Duc Kieu +3
Cross-domain offline reinforcement learning (RL) seeks to enhance sample efficiency in offline RL by utilizing additional offline source datasets. A key challenge is to identify an…
Hybrid Cross-domain Robust Reinforcement Learning
Linh Le Pham Van, Minh Hoang Nguyen, Hung Le +2
Robust reinforcement learning (RL) aims to learn policies that remain effective despite uncertainties in its environment, which frequently arise in real-world applications due to v…
Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer
Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal +2
Decision Transformers (DT) play a crucial role in modern reinforcement learning, leveraging offline datasets to achieve impressive results across various domains. However, DT requi…
High Dimensional Bayesian Optimization using Lasso Variable Selection
Vu Viet Hoang, Hung The Tran, Sunil Gupta +1
Bayesian optimization (BO) is a leading method for optimizing expensive black-box optimization and has been successfully applied across various scenarios. However, BO suffers from…
Policy Learning for Off-Dynamics RL with Deficient Support
Linh Le Pham Van, Hung The Tran, Sunil Gupta
Reinforcement Learning (RL) can effectively learn complex policies. However, learning these policies often demands extensive trial-and-error interactions with the environment. In m…
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks
Dat Phan-Trong, Hung The Tran, Alistair Shilton +1
Black-box optimization is a powerful approach for discovering global optima in noisy and expensive black-box functions, a problem widely encountered in real-world scenarios. Recent…