5 papers · 1 filter
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…
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…